So I'll start out and I'll end with the people who are actually doing much of the hard work that is Harsha Surbith and Nisha They they put in the work in doing the coding and doing a huge amount of data curation and analysis as you will see and Then there are various members of the consortium who I will also mention later Okay, so let's consider some kind of pathway model This is a block diagram. This is not individual molecules These are each of those has got lots and lots of individual molecules in it so we actually had to work to come up with a way of in fact zooming in and looking at it I Said to them come up with a Google Earth like thing so you can zoom in and see that see how horrible it really is But do so in a manner where you don't lose track of the various pieces So you can zoom in on any one of these if you so desire and each one of them is extremely complicated So that was just about visualization. So this is how we did it some 20 years ago This was a much smaller model. It looks awful because we didn't have the the ways to zoom in on different parts of it But the problem is that for a long time People have been kind of stuck That is a size of model with maybe a hundred or so reactants and reactions Seems to be in where people have plateaued in their efforts to come up with this kind of detailed signaling reaction Kinetics-based model. So why have you been stuck all this time? So it's not because of computer power computers can do And even then could do pretty much much larger calculations It's not been because simulators can't do it the it's for the machine is just a matter of scaling it up It's not been because we lack the data or the capabilities to get the numbers What I think the the problems have been are the the following few Which is first of all these are all these models have been handcrafted. We've gone out individually dug up the various citations worked hard to fit them into the model and That takes a lot of time and effort Having done that if you want to use it in a different context or you want to mix it with something else That turns out to be another whole exercise in hand crafting and rederivation and that's not easy not been easy When you Builds build a model you would like to then say okay I can reuse it wherever but the trouble is that signaling pathways the chemical reactions involved in them are Sufficiently tied up so it's sufficiently interconnected that you cannot just take one model and plug it into another one Which would have been a nice clean engineering solution. It is harder than that and Finally and perhaps not the least It's extremely boring and extremely costly to go out and get the numbers Whether this means hiring a bunch of people to go out and mind the literature or what that means doing the experiments yourself Doing you know many many repeats at many many time points to get the numbers So all of these have meant that models have not really in my experience gone very much beyond a certain scale When you're dealing with detailed mass action kinetics Okay, so this is where we thought we would try something new Sanket which means signal in Sanskrit This is the signaling and neurophysiology Knowledge resource for expand experiments and theory. This is a horrible background, but that's okay We we like them. So this is now We've just got a prototype website up which describes which embodies the workflow that I'll be telling you about It's we've had the consortium has been in existence for some Some months now for getting close to a year. We've had a we have a regular newsletter We have members from all over India and in fact some from other places and we'd very keen to get other people involved as well So since this is a session on workflows, I'm going to focus then on the workflow that we have in the Sanket project So we start by picking some process some cellular process or neurophysiological process that we're interested in So let's suppose it's something to do with synapses and their plasticity Once you've picked a process, then you want to make a model of it You want to say that these are the mechanisms that we believe in We want to get some data to populate those models and then this part is where I'll focus most how do you make the model as reproducible as accurate as good a representation of all that data and And then once you've got the model, there's many many things that I'm sure you all know you would like to do with it which range from Making predictions about how the brain works how plasticity works to examining various kinds of disease and Diagnostics, I mean there's a lot of things you can do with a nice detailed model of cellular function Okay, so to start with We were all in different labs interested in different things So we went about picking processes based on things that we were interested in one of them, which I'll be talking about most is the autism that is a project to simulate autism So that is what I'll be telling you about in most detail But there's other people for example, so we thought not currently who's from ice I said Pune one of our institutes in India She's very interested in presynaptic processing And there's another grouping of people who industry in synaptic plasticity. Basically, we can expand the topics We would like to look at depending on how is interested in it. So that was what we picked the members of this group looking at the autism project are Listed over here and they're from different parts of different all over the place Frat the autism as all of you know, I'll just Remind you very briefly One of the major causes of it is is is fragile X syndrome There's what happens is that there's a nucleotide repeat which causes a little fragile dangling bit on your X chromosomes and This can lead in a fair fraction of cases to mental retardation the protein. That's been implicated fmrp has effects on translation a fair number of Dendritic mRNAs are in fact targets of this and it leads to different kinds of morphology in the Compared to the wild type the mutants tend to have long thin immature looking dendritic spines so this is the system we decided to look at and in particular we decided that we would look not at the Systems or cellular level. We look at the subcellular level. What is happening at the synapse? Where how is it that incoming synaptic activity is converted into protein synthesis? So that was the system that we picked and of course the other groupings picked other systems are the sets of pathways to look at So how do we go about making a model? What we did was first of all, we need the model Modeling framework in this case. We chose the simulator moose, which is partly because we have developed it But also partly because these calculations Certainly involve multiple scales of functioning ranging from the signaling pathways the molecular Calculations that I'll be focusing on but also looking at cellular biophysics and also because there's a synaptic morphology phenotype also on how the geometry of the cell changes To do this we dipped into a database docs, which has got many many signaling pathways Particularly to do with the synapse We took a model of synaptic kinases We took another model related to activity driven protein synthesis and because we are looking at autism There were certain specific pathways that we know from the literature that had to be incorporated so we took all of these things and stirred well and mixed up to get a really really big nasty model Which is the so that is the thing that I started out showing you So it's got the additional bits in there and we merged together the kinases and the various pathways involved in in Protein synthesis driven by synaptic activity Okay, so this is a big ish model. It is substantially larger than anything. We have tried before I know that some people may have tried yet bigger models But let's see let's see how we go along with this because the goal of this The next step of this as you will see is how do you make sure that this model has actually got his feet on the ground? That it's got some basis in reality Okay, so just as I just to reiterate each of those things is a fairly complicated block of reactions And we need to parameterize we need to specify numbers for every single one of those reactions every single one of those Concentrations has to be defined in some way or the other so that is our challenge And of course, that's not the end of our ambitions at some point We would like to include for example reaction diffusion. We'd like to include the stochastic processes That are taking place in the communication with the spines and dendrites We are going to certainly put in electrophysiology and calcium dynamics and morphology change But for now we have enough on our hands as I'm sure you will see in a moment Okay, so that was how to make the model Next question was how do we get the data now in a perfect world? We would have entire institutions at our disposal generating these numbers for us This is not so easy, but we do have some Activities going on in fact we have been able to tap into a consortium activity on our own campus Where they're working with human IPSC is human induced pluripotent stem cells Which means that basically you can take a wild type and disease Patients sorry wild type and disease cells Differentiate them into neurons and then study their physiology and chemical properties something you cannot normally do with human brain tissue So there's a bunch of things we have begun to do on them We only have a little bit of data from this at this point. We would like to get human slice We actually have a line into a hospital which Processes such things so we hope it in due course to be able to do that that we haven't yet gotten going Mouse tissue culture. There's a lot of things that we can do with that and mouse slice now as you heard Right at the beginning of the of the of the day that you know mice are not monkeys and monkeys are not people either and Certainly the the what we have in a dish is not really representative of what's going on in your head But what we the best we can do is to try and get a few Sample points and try to interpolate or extrapolate to figure out what might be going on in the in the actual brain in the human brain So this is how we're approaching it the other side of it is to go to the literature and the literature is vast and voluminous and Extremely hard to parse extremely hard to extract numbers from so this is a job that Nisha in particular has been involved with She has so far curated Some 230 to 250 experiments Which I'll show you about in more detail and these are going to be the fundamental constraints that define our model so and one of the tools that we have in the in the Fine sim project in the in sorry in the Sanketh project is in fact a way of taking Experiments from the literature and sticking the numbers together Putting in as you will see the the aspects of experiments that need to be replicated by the model Okay, so that was the first two steps of the workflow now We come to the heart of it Which is how do you once you have this model once you have these experiments codified how do you get? How do you get to improve the model? So They're various components for that. There's of course the simulator you need to be able to run the calculations then there's fine sim, which is a project that I actually spoke about In a previous meeting in I NCF meeting And which has been published. So what this does is it allows it to it specifies a way of codifying? experiments and To take those codified experiments and run them on the model So you take the stimuli that were given in the experiment and you apply them to the model and then you compare the model outcome with what happened in the real experiment and you can do that from the web interface which can also manage this Growing database of experiments and then we run all of this through something we call horse horse hierarchical optimization of system simulations and What this does is it deploys the fine sim numerical engines the calculations of fine sim which again lie on on moose and then it can run these things in parallel and It deploys these to do the optimization using some standard algorithms, and I'll be telling you about these different steps Okay, so fine sim is this framework to integrate neural data and signaling models It's got its own website, which is all part of the SunKate portal and the approach is as follows So here's our model which I have described to you For the experiment we need to take the stimuli that were given what were the prop? What were the conditions under which the experiment was done and we also need to have what were the readouts? What were the outcomes of the experiments? So we put all of these things into a database we have a database of models We have a database of of the experiments and then we run the calculations on it And we compare the simulation output with what the actual experiments gave us and we can then compare the The real versus the the simulated results and use that as a score to decide how to improve the model So this is the flow chart for Doing the calculations within fine sim So there's a whole bunch of experiment types that fine sim now accommodates You can have the most straightforward one is you have your your system of Cells or or Reactions in a test tube and at some point you put in a reagent and you get some kind of time course of response of some readout Another very common thing which is used a lot in Biochemistry experiments as you do a dose response curve you apply fixed amounts of some stimulus and you measure how much response there is bar chart Experiments are common You can also do things in the electrophysiological domain. You can do current or voltage clamp experiments. In fact, this is Sort of under sampled version of the Hodgkin-Huxley Paper from 70 years ago You can do standard Potentiation kinds of experiments and many many more so these are all codified in in the in the in this workflow and Now we can codify it on the web You can run it from the web and in due course very soon. We'll be able to optimize it also from the web And I'll tell you a little bit about that Okay, so let's get to the optimization part which is the the heart of this So level one is we need to optimize sub parts of the model and This is something which can be parallelized because you can do each one At the same time you don't at this point We're just separating out each of these 40 or so different signaling pathways and you can do the optimization of them individually So that's nice Level two you want to take these modules and look at the crosstalk and so we need to optimize for the cross reactions That is a little bit harder to parallelize But some aspects of it can be done and level three we want to do multi-scale calculations. That is we may want to Optimize for when you have certain reactions occurring say in the dendritic spine or in the spine head and others happening in the dendrite So now you have to cross look at the crosstalk between those and so this or for that matter between the electrical activity and the chemical activity so each of these things can happen in In in a hierarchy and the reason one other reason why it's important to do it in a hierarchy is because if you have if you have Multi-thousand parameter model and you try to optimize all thousand or so of those at the same time You're not going to get very far Those of you who done who try to optimize things will realize that even the best algorithms will run aground if you try to do that so Doing it in a hierarchical way, which is also fortunately how one does experiments Makes it feasible to do this Just a glimpse of this So you might be able to do a reasonable optimization for a small part of the model, but eventually you will need to fit in the whole model If you start with a single subset say any one of these and each of these has now been optimized You would take the individual reactions and you would take a bunch of experiments which happen to Probe those reactions which constrain the rates of all these possible reactions then once you've decided the Reactions once you decide the experiments you figure out which parameters you permit your optimizer to tweak and those the ones in in red and Having done that you you unleash your optimizer, which is you know a fairly standard algorithm To optimize these you can assign different weights to say which experiments you want to assign more credibility to and then you turn things Turn the handle basically you let the the computer turn away at this And run the calculation. So basically what you're doing at this point just envision it you're running You're you're specifying an experiment. You're running the experiment on a model You're comparing the experiment output to the model output and you're giving it a score and you're doing this in parallel for a whole bunch of different experiments which all engage these pathways and each of so having run through all of these experiments you get a sort of summed score Saying that at this point the model fits this model fits all of these experiments to this degree Once you've done that you can go to the next iteration of the optimizer So all of this is done can be so all of these things can be done in parallel And then you go to the next step of the optimization process And so at the end of it you end up with some modified parameters You end up hopefully with an improved model and here's some examples. So this is where you started and This is so this pre optimization post optimization. So this one of the experiments Not such a great fit a much better fit. This one started out really terrible fit. It's still not a great fit But it's better than it was This one actually got worse But this one got better. So the model is Approaching not just one experiment, but it's trying to approach at the same time all of the experiments, which is why it's a somewhat touchy optimization problem and So in this manner, we have actually gone through the process So I should say Nisha has gone through the process of optimizing all of these individual modules Independently and the next step is to look at the cross talk. So this is where we are right now with this process of optimization and It's a similar kind of thing you pick up a set of experiments that define how the pathways interact and now you try and Try and optimize for those rate constants so We've recently had a very productive Google Summer of Code Interaction student being Hao Chen from Peking University He was a sort of Handheld by Surabit who is from from our group and so this I think is a kind of a nice illustration of the of the reach of the INCF that is we spoke to the neuroscience gateway people I mean Majumdar and his colleagues We had Google providing input for the Google Summer of Code project and of course the INCF brought it brought it all together Okay, so this has been the the the core of it how we went about the optimization I'll give you a glimpse of some of the things that we are already beginning to do with these models One for example is to compare what happens in the wild type version of the model with various mutant versions of the model So we can optimize based on Mutant parameter mutant experiments on mutants to get a different version of the model that applies to the mutant So for example, we know that in the mutant the levels of these different molecules Have been changed and we can run the calculations and say that for example for certain stimulus We get different kinds of responses. So this is a very early stage of Analysis, but we can already start to play with the models and say this is what happens in the wild type And this is what happens in the mutant Another thing that one can do is one can play with or examine how well the large body of experimental literature fits different theories of These mutants so for example, there's the Metabotropic glutamate receptor theory in blue our theory of a fragile X syndrome, but there's a competing theory also the cyclic ampi theory and Which of these is probably accounts for more of the observations? This is something we can now begin to play with and there's of course for pharmacology, there's the Enduring question of what are the best targets and what will be the side effects? So for example, if you were to believe in the m blue our theory, you would expect that this would be a useful target But then you would have all of these as potential side effects so we can calculate those Or if you believe the cyclic ampi theory, this might be one of the targets And then you'd have side effects in different parts of the model So these are now things we can put numbers to and say these would be the side effects if you put in a drug Which targeted that molecule of that molecule? Okay, so to wrap up then What I've done is I've just tried to describe to you the workflow that we've developed for this project This consortium it starts with coming up with a system that you're interested in Then one has to develop a model for that system of course closely based on a lot of data that pertains to that and then we have a whole System a whole workflow to take the available data Structure it and be able to use the data in a very systematic in a principled way to make a better model and Finally then it's up to the to the people in the project to figure out what they want to do with it so that is the the essence of this project and To wrap up I would especially like to thank Harsha, Nisha and Surbith who've been core to the project Jyoti, Vinod, the various other people have contributed their various collaborators and consortium members and funding from various people. So thank you Fantastic project. Congratulations indeed So far I've seen only big models which have been done within this ecocyc and the biocyc projects Which are the microbes and really small organisms They are still open systems, but it seems to be a bit easier to handle this openness than in your case So what's what do you do with the rest of the world? So to say when you have a model like that? So I'm not so familiar with those models, but are those more the gene regulatory networks? Yes Yes, yes Right, so one thing is that they have access to I would say a much more structured set of experimental data because you can sort of grind through those experiments in a You know a very systematic way you have the mutants you have the metabolic conditions, so that that really helps This is I mean certainly they've done an outstanding job on doing this But I think here we are up against a much more heterogeneous set of experiments And that was one of the big challenges that we had to face to come up with a way that you could take Very diverse kinds of experiments and still use them But the question is about the openness right because in case of microbes and small systems You know what kind of nutrition sir molecules are interacting with this system in your case. You're just a part of it It's true. Yes. Yes, so so how do you treat the openness? That's yeah, that's a great question. So this is this is the question you ask the person who's looking under the lamp post for the key Right. Yeah, you're looking there because that's where the light is. No, it's based on Our best judgment that is we take what we can see from the literature that these are key pathways that must be involved Which is why we incorporated a few additional pathways beyond the ones that we had started with It is very likely that as we go through this process We will say that okay, some interaction is simply not working with the available model So we have to extend the model. So that's a systematic way of doing it We'll know that is that is part of the part of the process any further questions So actually I would have one question just So I was wondering like these that the advantage of having these workflows is is that you can actually rerun? Yes, these workflows again and again. So from your experience What happens if you get new data and you get to optimize against an extended data set? How stable are these estimates in your experience so? at this point So generally, okay zero order is reasonably stable Every so often new data will show us that our existing model is inadequate In which case we need to go back and add some more interactions that are not there Currently, but the whole point of doing it this way is that you can incrementally add new data as it comes in Okay, if there are no further questions, let's There's one more in the find some workflow. I imagine there's there's parts of this that are very Specific to the kind of system that you're you're you're optimizing and then other parts that are more general right that could apply to maybe some a different kind of Experimental system or a different level of modeling to what extent are those Are those are those make like is there a distinction between him between those or is it kind of built end-to-end for this this kind of these kinds of models? so it's It's it's extendable The things that we put in were based on our general interest in looking at neurophysiology and the underlying signaling So that's why we have a range of things from the standard biochemical readouts to also the standard electrophysiological readouts and the slice LTP kind of readouts should more things come up that need to be incorporated we can we can do so the Commonality in all of these is that you specify the experiment you specify the experimental result You run the simulation and you can compare and therefore you can apply the same algorithm so the specification of the experiment has two parts you specify what was the Preparation so in other words what part of the overall model was necessary was used by the experimentalist and You specify what were the inputs so let's say a stimulus at such a time or a shock pulse at such and such a time and Then you also specify what were the readouts which could be a chemical readout or an electrical readout and That's the specification


Cardiac muscle cells have several characteristics that are different from skeletal muscle cells. Let's make a list of those characteristics. First of all, cardiac muscle cells have one nucleus per cell. This would be an awesome compare and contrast question on an exam comparing contrast the structural functional characteristics of cardiac muscle and skeletal muscle. So one of those characteristics is the fact that cardiac muscles have one nucleus per cell. Cardiac muscle tissue is striated. Do you remember what caused the striations in skeletal muscle? It was the presence of the sarcomeres. So because cardiac muscle tissue is striated, there are sarcomeres inside the tissue. And if you look down here, we've blown up a cardiac muscle cell, a couple of them here. And you can see that, yeah, we do have the myofilaments organized in sarcomere fashion. That gives you the visual of striation. Cardiac muscle cells are even more filled with mitochondria than skeletal muscle cells. Why? Because dog pounds, your heart started beating when you were 22 days old in your mama's belly. 22 days old and you get a little heart beating.  And that's like 100,000 beats a day. What? That's incredible. You need a lot of energy to sustain that kind of activity. And so we have, I think it said, a third of the volume of a cardiac muscle cell is made up of mitochondria. That's incredible. Other, there are a couple more characteristics about cardiac muscle tissue. One of them, cardiac muscle cells are branched. And this is something that you can actually see if you look at the histology of cardiac muscle tissue. But take a look at this. This is a cell and here's an end of the cell and here's an end of the cell. And did you see how it totally, like, branched? And this is a structural characteristic that enables cardiac muscle tissue to be stronger. You want it to be strong because if your heart rips apart, oh, that's probably not a real great idea. And if you think about exercise or stress or bears chasing you around in the woods, it's definitely, you want your heart to be able to increase its heart rate and increase the amount of blood that it can pump through your body without tearing. You really don't hear about heart muscle tears that often. You definitely hear about skeletal muscle tears.  That really stinks. But if you tear your cardiac muscle, it's going to be a bad situation. So this branching is one piece that makes it just stronger and less likely to tear. The other thing that makes it stronger are these structures called intercalated discs.  Look, here's one right here. This is an intercalated disc. It's where two cardiac muscle cells connect to each other. And you can end up with this visual of, like, a literal line between two cardiac muscle cells. This is the other one of the characteristics that helps you identify cardiac muscle tissue in the microscope. But these intercalated discs have, number one, they're made of structures called desmosomes. And these are, like, super strong staple connections. Like, they weld the two cells together at the intercalated disc. The other thing that is found in an intercalated disc, doggies, oh my doggies, gap junctions. And remember, gap junctions are just, like, tunnels that allow cytoplasm. Okay, we're going to make a little bit of yellow cytoplasm. They allow cytoplasm to move between cells. So if you've got a whole bunch of gap junctions in your intercalated discs, you're serving two functions. Number one, they're holding the muscle cells together. And number two, they're allowing cytoplasm through. This is functionally critical. Your heart will not do its job if those gap junctions are closed. Another characteristic of cardiac muscle tissue that's different from skeletal muscle tissue, is that you do not need a neuron. Okay, I'm not sure why I'm drawing this neuron. You don't need neural input in order for cardiac muscle tissue to contract. Cardiac muscle tissue will keep contracting until it runs out of energy. And I just have to show you, I probably should turn off the sound here because really there's no point in listening to my Marvel about this turtle that he killed one day when he decided he was hungry for turtle meat. And so he cut out the heart of the turtle, was cleaning the turtle, and then realized, look at the heart. It's still beating. And hopefully you're like, dude, really? Why? How's that even possible? It's possible because even though we've taken this heart out of the turtle body and it has no neural input whatsoever. It's not connected to the brain. It's not connected to the blood supply. The cardiac muscle is able to generate its own action potential and that allows it to continue to beat. This is pretty phenomenal. Oh, that was a close call. I always get scared when we get to the end of a YouTube video because sometimes things come up that you really don't want in my YouTube video. Okay, so there's two different kinds of cardiac muscle cells. There are contractile cells and auto-rhythmic cells. And we're going to look at contractile cells first. Both of them respond to action potentials. Both of them contract when an action potential tells them to. So let's take a look at contractile cells first.


EU mission in Armenia, targeting Russia rather than Azerbaijan. Recently the Armenian parliament ratified the agreement on the status of the EU mission stationed on the border in Azerbaijan. As is known, the mission was established in January 2023 and in December. The number of mission participants increased from 138 to 209 people according to Azerbaijan news media outlet. Currently the US joining this process and planning to send its soldiers to Armenia as part of the EU mission actually means that the West is creating its own military base in Armenia. All these processes take place on the borders of Azerbaijan, so many think that this format is directed against Azerbaijan. However, member of the Azerbaijani parliament, Fazil Mustafa, thinks that this mission links with Russia rather than Azerbaijan. Speaking to Azerbaijan news on the issue, the Azerbaijani MP noted that Armenia takes these measures because it feels uneasy. He pointed out that Armenia is right in a certain sense from its own point of view. The MP underlined that the issue should be approached on the basis of relations with Russia rather than with Azerbaijan. Yerevan emphasised intensive contact with the West. However, they probably calculated how dangerous and risky these relationships are. Otherwise, the presence of the EU mission or the US mission in the region can create great cataclysms for Armenia. Because a country that has built such deep relations with Russia suddenly makes a U-turn and approaches to another power centre, the protective capabilities of this power centre are also not at a high level. Therefore, this issue is still one of the factors that show that Armenia itself is a bit adventurous. This is a dangerous adventure and it is difficult to say how Armenia will eliminate its consequences. He said, Fazil Mustafa pointed out that the fear from his society and takes concrete steps towards peace. As I mentioned earlier, the increase in the number of military personnel from the West is a matter related to Russia. For Azerbaijan, Armenia is already a country that maintains a military base of a foreign state in its territory, as is known except for the military base in Gyumri. The borders of Armenia and the airport are guarded by the military of another country, not by Armenia's own military. Now, the arrival of new foreign power means that there will be a problem between the previous power and the newcomers. Therefore, this is more relevant to the relations between Armenia and Russia. Fazil Mustafa opined. The MP pointed out that the creation of the West's military base in Armenia means a military conflict with Russia. Republican congressman calls for resignation of US House Speaker over blocking aid to Ukraine. Marjorie Taylor Greene, a member of the US House of Representatives and Trump's ally, has initiated the resignation of a fellow party member, House Speaker Mike Johnson, who is delaying US aid to Ukraine. The Hill reported this. According to an informed source, Greene has filed a motion to remove Johnson from power. The same procedural step that led to the resignation of former Republican Speaker Kevin McCarthy in October 2023. This was preceded by the House of Representatives approval of a US $1.2 trillion spending package to avert a US government shutdown. On Steve Bannon's podcast on Friday morning, Greene accused Johnson of giving too much away to US President Joe Biden and Democrats at government funding talks. Whether there will be enough votes to remove Speaker Johnson is unclear. According to The Hill, this is due to the fact that a number of Democrats who unanimously voted for McCarthy's resignation in October say they will support Johnson if he continues to make bipartisan deals with Biden on issues such as government funding and aid to Ukraine. Johnson refused to consider the Senate approved support package for Ukraine but promised to work on a House version of the bill when Congress returns to Washington in the middle of next month after a recess. Earlier, Mike Johnson, Republican Speaker of the United States House of Representatives stated that the bill for supplementary funding for Ukraine would be considered as soon as the federal government's financing issues are resolved. US House Speaker Mike Johnson effectively agreed to unblock the decision to provide aid to Ukraine but with significant changes as a House of Representatives bill and in the form of a loan or lend lease. He also admitted that aid to Ukraine and Israel would still be divided into separate bills. Any new bill will have to receive enough votes in both the House and the Senate. Russian hackers attempt to deceive German politicians. Russian hackers and spies attempted to deceive representatives of German political parties using fake dinner invitations according to Bloomberg. Hackers from the APT-29 group linked to the Russian Foreign Intelligence Service were previously known for attacks on diplomatic institutions but this time they focused on political parties. The material writes that this shift indicates a broad threat to European and other Western political parties across the political spectrum. Chief Analyst at Mandiant Intelligence John Holtquist said he is concerned that this may not be an isolated incident and other organizations may become targets of hackers in the near future. The attack involved Russian hackers posing as representatives of Germany's Centre Right Christian Democratic Union Party sending fake dinner invitations via email claiming the dinner would take place on March 1. The invitation encouraged recipients to click a link which directed them to a malicious file. The report added that the shift of Russian hackers to attacks on political parties aligns with Kremlin interests in understanding decision-making processes related to Ukraine and other issues. The article notes that some of the hacking tools used by Russian spies in the attack on Germany were first detected by security researchers at the end of January 2024. Outside of Ukraine there is no bigger priority for Russia's intelligence services right now than monitoring changing Western political dynamics said Mandiant's Chief Analyst Dan Black. He believes this attack is not just aimed at targeting the Christian Democratic Union Party of Germany. He thinks it's part of broader Russian efforts to find ways to undermine European support for Ukraine. Recently a series of cyber attacks by hackers were recorded during which the perpetrators sent Ukrainian servicemen messages via the signal messenger with malicious software about recruitment to the third separate assault brigade of the armed forces of Ukraine and the Israeli defense forces.


So, first up, I want to introduce you to Casey Schultz. What up, Casey? Casey Schultz is a visionary thought leader and influential advocate in the world of impact investing. She works prominently at the intersection of finance, business and social responsibility with an unwavering commitment to creating positive change and driving social environmental impact. Casey leads the FR Bigelow Foundation Impact Investment Portfolio, a place-based impact investing portfolio focused on improving the lives of the Minnesotans. All right, Claude Grzinski.  Claude Grzinski is the CEO and managing partner at the Equity Alliance, a New York-based fund that invests in venture capital firms and early state ventures run by women and people of color. Claude is also the founder of two media companies, Trace and True Africa. Over the past two decades, Trace, which was funded by Goldman & Sachs, was successfully sold to European investors and has become one of the most popular youth culture media brands. Also, True Africa is a Google-funded media tech platform championing African voices and innovators globally. Welcome. All right, and last but certainly not least, Jennifer Nundorfer. Come on up. Jennifer Nundorfer is an operator-turned-investor who's been investing in early-stage startups for the last decade. She's a co-founder and managing partner at January Ventures. It's a pre-seed firm that works on B2B startups and democratizing digital transformation in the world of health and climate. January Ventures has invested in 60 companies to date and closed fund too in March 2002. I also love Jennifer's Cuban American, and she is one of the few Latina GPs in Venture, and she's committed to demystifying Venture Capital for diverse audiences. So I think that's one. All right. So I'm excited to have you guys all here, and I think a great place to start is we all have our definitions of diversity and DEI. I think it's nice to set the tone by asking, what does DEI mean to you? Jennifer? I'll say I could talk on this question for a while, but I'll keep it short. First of all, thank you to Socap for having us. I'm really excited for this discussion, and Ashley excited for your leadership as we go through this discussion. Diversity and DEI is really core to what we do at January, so we've spent a lot of time thinking about this. The venture capital of the industry that I'm in is not known for diversity, and that's much of why we founded January, and I'll talk more about that. But for us diversity, it all comes down to the diversity of thought of the founding team and the company that they are building and why we believe that will lead to superior outcomes. So when we think about diversity, it is race, ethnicity, gender, geography, pedigree, or lack thereof. The experiences both lived and professional that our founders have had, and so we think about this on a variety of dimensions, and it's something that we're really focused on tracking both to hold ourselves accountable, but also to tell our story to our investors and to future founders. So that's how we think about it, Ashley. Yeah, that's wonderful. Claude, how about you? What does diversity mean to you? Why does it matter to you? For me, I've thought of this through so much, and I've actually been able to encapsulate this whole work on diversity, which basically is my entire adult life. I focus on this issue of diversity, and the way that I think about it now is just one word, and that word would be underrepresented. And why underrepresented? It's just that there are certain people like myself, like the people that we fund, who are used to always being underrepresented in most rooms. When I was a young founder and I raised $15 million series A from Goldman Sachs, I was the only black founder at 30 who was able to be in that room, and at the beginning I was so intimidated by the mystique and the power and the prestige of the institution that it almost felt like I was such an outlier that the whole concept of being underrepresented ended up being something that drove what I did, and what I'm trying to do now is to make sure that underrepresented voices are heard and feel like they belong as opposed to almost feeling sometimes like they're imposters. That's a good point. I really like that you were able to frame it into that one word. Casey, how about you? Well, personally I would say that everything I do is through the lens of like, how do we create the most equitable and thriving communities? And in order to do that, you have to create opportunity and access to everybody in your community. And we know that that is not the case currently, and with that as a building block, we're able to take that up the value chain or the levels of investment all the way up to who are actually making these investment decisions, where are we investing our community's money? We want to make sure that it aligns with our values and our mission. And then as we're going to talk today, we know that that also drives better returns, which is supporting our community. Yeah, I'm wondering if you guys can share more about like, how you actually got started in this work and how you began the process of helping DEI work to even align with the mission of the organizations you work for, the organizations that you've been a part of. And Casey, I think I want to start with you because like, if somebody was in this room and they wanted to get started with this work, how would you suggest that they move forward? Like, I don't know, I know you've done some survey work. I don't know if that's a great place to start. Yeah. And so St. Paul and Minnesota Foundation is the largest community foundation in Minnesota. We have $2 billion in assets under management. And when my boss Shannon O'Leary came in as the chief investment officer, she jokes that she came into a portfolio built on golf games and steak dinners. And when she was looking at where our community's money was going, it was going to investments that were directly canceling out the work we were doing in grant making. So here we are putting money out in the community to try to solve our most pressing issues. And then we're investing our money in the things that are causing those issues. And so she was, she immediately went to the board and said, we need to be more mission aligned. We need to make sure that our investment dollars reflect our values and our mission. And so I would say the first step when you're thinking about like how do you even incorporate diversity, equity and inclusion into your organization is get your stakeholders in a room and say, hey, does this align, you know, we need to make sure we're aligning with our values and how are we going to do that. And so that I would say is like the first step is just acknowledging that you need to make sure that where you're investing your money is aligning with your mission. Yeah, I like that aligning, aligning the actual dollars to the actual, you know, impact that you want to see.  But how did you get started in this work? And if somebody is wanting to get into this work, like what would be a guidepost that you could give them? Well, I may not be the best example for that because I am a bit of an accidental venture capitalist. My whole identity was kind of built on being a first generation founder and I was always a media entrepreneur. But I always believe in the fact that certain people you meet along the way will have a huge impact on your life. And having sold my company in 2010 and just a joke that I retired in my late 30s, I just started angel investing. And I started teaching at Harvard, which I still do, which has been really rewarding, but I never thought I'd become a venture capitalist. But along the way, I've been building a very strong relationship with one of my mentors really for the past 20 years. And that mentor is Dick Parsons. And Dick Parsons, when I met him, I was a media entrepreneur, I was running my company Trace. At that time, he was the CEO of Time Warner back when it was the world's largest media company. And for me, that was a significant thing because I'd never seen a black person running a Fortune 100 company. And he took me under his wing and I became really close to him after he became the chairman of Citigroup. During the financial crisis, he would ask me, what is it like running a small business in this environment? This was the too big to fail moment where it was do or die. We might remember how tenuous the whole thing was. And when he became chair of the Rockefeller Foundation, he was very much all about impact investing. As a matter of fact, he hired Judith Rodin to be the president of the Rockefeller Foundation. She's known for having quote-unquote coined the expression impact investing. And I remember that Dick was a little bit frustrating because the Rockefeller Foundation was not doing enough impact investing and they were perhaps a little bit too safe. So he would always use me as a sounding board. And two years ago, he called me out of the blue and he said, it's time. I said, it's time for what? He said, it's time we set up a fund because I've just read an article that states that in asset management, white men manage 98% of the funds. I had no idea that the inequity was at that level. And he said, I'll be the chairman. You'll be the CEO and managing partner. You'll have to do all the work and raise all the money, but you can count on me. And so here I was and, you know, looking at this model, we're a fund of funds that also co-invest alongside the funds that we back. And we started with a fund one in 2021 and now we're raising fund two. That's amazing. That's amazing. I think like what I took away from what you were just talking about was sometimes it's that staggering statistic that gets us into alignment. And Jennifer, how has it shown up in your work in terms of the alignment with the EIN and how you got started in this work and how you've been able to sort of have some synergy there? So for me, there was a staggering statistic. Yeah. And it also was something that was highly personal. So my partner and I, we are two female GPs running a venture capital fund. When we started with something like 6% of GPs and, you know, allocators, decision makers at the venture capital level were women. So we were in the vast minority, but it really came out of our experience having been operators in the tech world. My partner, Maureen, was a founder. And our experience and we met at Stanford Business School. We were here in Silicon Valley and yet even in the heart of all of this, what we saw was that the staggering statistic was that women, female founders raised just 2% of venture dollars. And when we looked around, first of all, that's a terrible statistic. But second of all, we see these women in our networks who are starting unbelievable companies. Like, how is there this capital, this allocation? And so while it was staggering, it also was like, man, this is a huge opportunity. And we saw the same dynamic among founders of color. And frankly, I left Silicon Valley and then moved to the middle of the country and saw that same dynamic there.  That was not what I set out to do. But as I just saw in my experience that there were these amazing founders who were outside of either the traditional venture capital networks or the traditional mold of what a venture founder looked like, which is a white male from a certain school. It became this opportunity that was just too big to ignore. And frankly, given Maureen and my personal experience, we also felt deeply motivated to go out and work with these amazing founders and solve this huge point of friction around the capital that they were able to access. One of the first things that we did at January was go out and survey early stage founders. We knew that they were going to be our customers. So it was like, well, this is kind of our voice of the customer research. And what we found, this was five years ago. We've now done this study every year since then. But we found in that first study was that for every dollar that a white male founder raises at the early stage. Female founders raised 37 cents and black female founders raised just two cents. And so when we saw that, it was like, we have to go do this. And we thought about going to a larger fund. But the reality is, and we'll talk about how one can pursue this sort of strategy, we really felt like we needed to do this with values that were true to us. Our core values are transparency and access. It's pretty unique in the venture world. We wanted to go out and just build a fund on a fundamentally different sort of network that we believed could support source and then support the founders that we believe were building the future. Yeah, that's great. I think all of us on this stage probably share similar values when it comes to why we think diversity, equity, inclusion is important. But we also probably share philosophy on impact and wanting to see impact. And I know as a journalist, I'm always like, show me the numbers, show me something. So can you describe maybe the impact of DEI on portfolio returns and how have you measured those returns and get as specific as you can as specific as you're comfortable going. But can you describe the impact of DEI on those portfolios and then also how have you measured the impact when it comes to those returns and anyone can popcorn and take it first? I'm happy to jump in. So we have St. Paul Minnesota Foundation, which has a $1.7 billion multi-ass endowment portfolio. And that's where we've really put a lot of work into how do we make sure that we are investing in diverse teams. And what you will find often is when you're talking to asset managers, whether they're private credit or they're private equity, they're like, we're diverse. We have four women on our team. And then you're like, show me your org chart. And they're like, it's a secretary and a woman who runs HR and our attorney.  Because if you have people who all went to the same school all look like get all their news from the same source, you're going to really suffer from group think. And so that's something that we spend a lot of time digging in with our asset managers. And we created this very in-depth diversity, equity inclusion due diligence questionnaire that we send out to all potential investments. And we actually shared it with the UMPR. You can go on UMPRI's website and download it if you're interested in having it. And so that's the first, like, toe in the door. And we always say, we know there are a lot of legacy asset classes where it's just not diverse. So we're really measuring improvement over time. And then so we send that first DDQ. And then we send it every two years, a diversity survey that all of our asset managers have to complete. And then we give them a letter score.   And it actually has like created program. Like a lot of these shops have created diversity equity and DEI programs where they're like, OK, we got to figure out what is broken in the cycle. Why are we losing so many women after, you know, as they're advancing through our shop? Why are we losing so many people of color? And they've created programs that actually solve that problem and are going to pay dividends. And so by working with those types of asset managers who actually care about this program or this problem, we are finding that they are getting more diverse teams are getting more diversity of thought. And I'm really happy to share that we our foundation is in the upper top death style of all community foundations with $250 million in assets under management and more in the US. So we're seeing like firsthand that this this program is is paying dividends and improving the returns on our whole portfolio. So it's it's it's very a very effective way to generate alpha. I love that. Claude, how about you? Do you have an example of or like a case study or an example you can share that reflects the impact of DEI, especially as it relates to, I don't know if the right word is out performance, but it's doing good. That's what we that's what we want is out performance. I'm glad you went there without performance. So, you know, the interesting thing that happened for me, and I'm glad I'm speaking right after you, case Lee, is I used to go to Minneapolis all the time, because when I was a media entrepreneur, the Target Corporation was one of our largest clients. And I just became really friendly with a lot of Somali American cab drivers that would take me from the airport to the Target office. And then when the George Floyd thing happened, I just really couldn't understand why and how it could have happened in the city like Minneapolis, which I always consider to be one of the most progressive places metropolitan areas I've been to in America. And then I started reading everything I could read about Minneapolis. And I came across one statistic, which was the ratio of ownership. And you compare that the black community, only 28% of African Americans in Minneapolis are owners of their housing.  And that just, that explained the inequity. And so I always look at the big societal changes that are coming and how we can contribute. And when we talk about our performance, so as I said earlier, we invest in VC funds, but we also invest in some of the most promising portfolio companies. So our very first direct investment in a fintech called a SUSU is very much just focused on solving that issue. So we only invest in women and people of color. And this company was created by two founders who came to the US as I did as immigrants. One of them came from India. The other one came from Nigeria. And they came up with a really simple solution, which was to help renters build their credit score in order for them to get on the properly ladder and then step two to become owners. Now, as we look to help democratize access to capital and help to build more pathways to economic mobility in America, the housing issue is absolutely huge because now I'm an owner. I own my apartment in New York and I can take out a home equity line of credit. You know, I could, if I didn't have savings, I could pay for my son's education in that way. So a SUSU, which is a company that we invested in in July of 2021 in their series A, six months later, they raised a series B at a $1 billion valuation. So we got a 15x return in six months. But it's not just about the fact that we're going to make a lot of money with this investment. It's the fact that they were able to sign a deal with Freddie Mac and Fannie Mae and they're operating all over the United States, all 50 states right now to help renters become owners. So for me, when I talk about impact, that's very real impact. It's not theory, it's very real. Oh yeah, that money's real. I felt that impact in my chest right here. Jennifer, how about you in terms of measurement and what have you been seeing portfolio wise? Yeah, so I think one thing that I'll start with and then get to measurements, like just to underscore what I love about the example that you shared, Claude, is like the example of the SUSU, they were familiar with that pain point, right? And their own lived experience made them realize this is a problem to be solved. And I think that is part of what we're excited about with the founders that we are investing in. Their experience gives them a different perspective on problems and helps them unlock opportunities that maybe a more traditional founder wouldn't. One example is a company we did their precede, a company called Athena, which is modern compliance training. It's like the least sexy space, right? It's the stuff that, and actually the founder when I met her, she was like, tell me about the last time you did compliance. I was like, well, it's been a while, because it's been a while since I've been at a big company, but you know, I was on the phone and just clicking through and my HR partner's calling me saying, like, you got to get this done today. But very few people absorb that content, right?  And the founder, she was a woman who had been in large companies, but she also was a female vet, so she had been in the military. She had had a really interesting experience with both training and compliance and took that and applied that to something that literally every company has to do. And that opportunity may not have been visible, or that pain point and solution may not have been visible to a more traditional founder. And there's both impact in terms of who she is, but also the way that she is impacting people who go to work all across the world. You know, in terms of the measurement, we made a pretty deliberate decision when we went out to market and started to build January that we were building a returns-driven fund. We did not initially go after funds that were, or LPs who were focused on impact investing because we wanted to be very clear that this was not a concessionary strategy. And so we measure ourselves based on the typical metrics that a venture funder is getting measured on, right? So TVPI, the total value that we create in our portfolio, DPI, the distributions that we send back to our LPs, IRR, and so that's what we're tracking against. And what's exciting to see is our strategy is performing. We have top quartile metrics according to the Cambridge benchmarks. And so now, when we started January, we were going out and saying, here's what we want to do, believe in us. And now when we go out, we're saying, here are the metrics and the performance that we're driving. Here's the underlying performance of those companies. And it's a much more powerful story. And to bring in some secondary data, the data is very clear that diverse teams outperform non-diverse teams. There's been a bunch of studies, like BCG released a study that showed specifically around female founders that having women on a founding team increases the revenue per dollar invested by 2X. In particular in a market like this, where we're focused back on fundamentals, that's huge. And then at the public company level, what you see is that when a female CEO replaces a male CEO, the stock price on average goes up by 20% given the performance of that company. And so I think we're at this point, and one of the reasons I'm so excited to have this discussion with, you know, allocators who are also talking, allocators like both of you are talking about the metrics, is that the data is pretty clear that diversity on management teams does drive returns. And now it's time for all of us to evangelize that and talk about how we operationalize some of those strategies. Yeah, I think what's really important about what you guys are saying is like I'm connecting to the powerful storytelling around ASUSU and Athena and the work that you're doing in Minneapolis and also the data, like the facts are clear, this is the impact of diversity. But whenever you are in the process of giving and receiving money and whenever capital is involved, there's still critique around DEI. It's not critique-free. There's still criticism around it, even with the data, even with the powerful storytelling. And so I guess my question is how are you navigating the tension around DEI investment, particularly maybe when it comes to the conversation lane of like why use that as a frame? So I hear what you're saying, but also I know that people are still like also why use DEI as a frame. So if you can talk about that tension, if you have an example or maybe how you've overcome it, how are you navigating that space? Yeah, I'm happy to jump in here. So to your point, and we're seeing it, especially on a national stage right now, there's literally an attack against diversity equity inclusion and using the policies and laws that were actually created to make it more equitable and especially with the black community have more access. Those laws are now being used against those communities and it's a travesty. So something that we did at the foundation is we knew that we needed to codify our policies into our investment policy statements so that anybody coming on after us, any new board member, we did so much work bringing the board along with why diversity equity inclusion is actually a fiduciary responsibility because of everything we talked about.  You know pension funds are really bad at this. You should be, it is your fiduciary responsibility to be investing in diverse asset managers or diverse teams. And so we actually changed our investment policy statement to clearly state that we make all of our investments through the lens of diversity equity inclusion and environmental, social and governance. And that got voted in by our board this May. So no matter like when my team leaves, when we get new board members, anybody coming on, it's going to be very clearly stated that it is our policy that we invest this way. And we have yet to have any sort of pushback from the community or have that bloom guy come and sue us. So hopefully that doesn't happen. But I think just by codifying and saying, no, this is a policy, it really does hopefully make it more difficult to ever change the way that we're doing that investment. My perspective is this kind of DEI mandate became so trendy a few years ago that as you know, many people kind of jumped on the bandwagon because all of a sudden it was DEI that they had to push. And as somebody who spent, again, his entire career in the DEI space, I've met a lot of DEI frauds. What do I mean by that? They have not been directly impacted by the inequality that comes with a lack of diversity, equity and inclusion. And this is really problematic. And so in the work that we do as investors, we really study the lived experiences of the people who are pushing these policies. And if I look at my own story, I came to America as a penniless immigrant. And I remember I didn't have any credit because most immigrants don't have any credit. And similar to the two founders of Asusu, I was also subject to predatory loans because I didn't have credit and that was the only way I can get into the system. I was directly impacted by that. And so because I know the pain that comes with getting these credit cards that overcharge you and just keep adding fees, and at that time I was just really living hand-to-mouth and every penny counted, I'll never forget those experiences of just coming in as an outsider, trying to become a part of the American capitalistic system and being impacted. And now that I'm in a lot of elite circles, I can see how certain people just have no idea what I'm talking about. I mean, some of my students at Harvard, I see them now, this is my seventh or eighth year teaching, they've never had to work a day in their life. And they probably will never, ever have to work because of the inherited wealth. And for them, the whole DEI thing just becomes a construct, an abstract thing. And so I look for people who really understand the health inequities, the financial inequities, and all these things that need to change for America to become a more inclusive society. Yeah, I think similar to Claude, we are unapologetic about our focus. So as it is becoming a more polarizing thing, it is clear who is supportive of what we're doing and interested and wants to learn more and who isn't. But a lot of what, for the people who are on the fence, let's say, or questioning, part of it goes back to that data piece. Let's actually talk, if what you care about is returns and you're worried about, isn't DEI distracting, or is it, one of the questions we get a lot, well, with that strategy, are you really finding the best founders, which makes my blood boil? Yes, and let us show you the data. And one of the things that's interesting, one of the challenges of DEI, or of that framing, is that we find with our founders, they don't want our money because we invest in female founders, founders of color, founders outside of traditional networks. They want our money because we think they're the best founder. And so there is this interesting framing, and I get that, as a female fund manager, I want capital from allocators because they really believe in our strategy and they think we are the best people to deliver on that, not because we're like ticking some box for them. And so where we really come down to is just framing it as the opportunity. One of the things that I think, so if we think of DEI was trendy for two, three, four years ago, and now there's sort of this backlash, what the opportunity that that creates for a fund like ours and for allocators is that there has been a lot of pullback. In our founder survey this year, which just came out last week, what we saw was that female founders, founders of color, founders outside of the coast felt like they can feel investors pulling back and retreating to their networks, which only exacerbates all of these stats that we've talked about. And so when we get those folks on the fence of like, well, why is this your strategy? It's like because now there is an even bigger opportunity than there ever was. And so our strategy has been fight it with the data, the opportunity and win them over based on what they care about, which maybe in that case is returns and we're slowly chipping away at it. I think it's a constant conversation and one where it needs to be from a variety of different sources reinforcing that same point. Yeah, I think that's good. I think it's honest to say it's complex and that they're gray areas and that people are still challenged by the concept of saying full on, this is an investment strategy and this is what we're doing with it. Okay, so I've asked questions. I would like to open it up to the audience. Is our volunteer here? Do we have questions? And if one comes up, feel free to like jump up and speak to the room. Okay, so let's see. All right, so even though the data shows that returns are better in investing in diverse teams, Capital and Wall Street does not invest that way. Why? Why? Okay, here's the deal. So when you're talking about emerging fund managers, like Jen, when you're launching your first fund, and you are trying to get into institutional investors, there are so many gates and gatekeepers. It's so hard to, one, get your foot in the door with asset allocators. So take our portfolio, for example, we have 1.7 billion dollars in assets under management. My minimum check size out of that portfolio, $5 million. If Jen's fund is only a $10 million fund as her first fund, immediately I'm like, well, I can't be 50% of your fund. So already you're cutting off most institutional investors or family offices. They want to see track records. They're like, are you institution-dollar-ready? So one of the things that we've done at the same problem, the Minnesota Foundation, we manage assets for a private foundation called FR Bigelow. And in 2018, FR Bigelow Foundation said, hey, in addition to all the grant making that we're doing, can we also improve our community with our institutional investment dollars and do place-based investing through the lens of diversity, equity, and inclusion?  And so one of the things that we do out of that portfolio, it's about $20 million right now, we work with emerging fund managers and we say, hey, we want to be your first institutional check. So we're going to actually bring you in. We're going to put you through a very rigorous institutional investor due diligence process where when you go out to Bank of America, Amazon, Wells Fargo, you're going to have the best data room they've ever seen from an emerging fund manager. And we're going to write a million dollars into your fund. And so we've done that with five emerging managers based in Minnesota so far. And that portfolio, that impact investing portfolio, has an 18.8% five-year annualized return. It is going like bananas, how well that portfolio is performing. So just one more point where it's like, removing the barriers for emerging fund managers who are diverse is also something that's really important to us who are asset allocators and especially in philanthropy. I see that as an integral role we play in solving a lot of these problems. Yeah, I think a lot of investing in Wall Street is the same. It comes down to networks and pattern matching. And that's particularly true in venture. It's true across the board. And this is something we've thought a lot about. I don't think you can take those things out of the process. And a lot of the work that I think has been done in this space is like, okay, how do we totally do away with networks? And how do we, it's just somehow, it's how people work, right? It's how you source investments. It's how you underwrite risks. But what I think we need to make sure to do is how to create on-ramps into those networks. And on the pattern matching side, how to help, let's say, founders in this case, or fund managers, in case you talked about how you're doing this with fund managers, like learn the lingo, right? And pitch in a way that someone on Wall Street can say, like, okay, this founder may be different than the founder I typically invest in, hearing some of the signs that I typically pattern match for in a pitch. And so a lot of the work that we do with our founders who might be first-time founders who don't have a lot of friends who have raised venture capital, because the reality is, like, on the golf course, there's a lot of this talk of, like, oh, just say XYZ, like, go talk to this person. There's a lot of that informal help. We do a lot of that work to help our founders. If we write that first check, give them really warm intros for the next round, and get them ready to go have that conversation so that it, so that someone can really hear it. And there's obviously all the work to be done to unlearn the biases on the part of the allocator. But there's also a lot of work that we're doing, the responsibility that we feel as their investor to help get them ready for that conversation so that from a networks and pattern matching process, they have a fair shot because they're up against a lot. I don't know what you'd add there. Being up against a lot is exactly how I would start this. And I always try to contrast the experiences of people who are in the different worlds that I navigate, right? I talked about, you know, the fact that I'm still very connected to people who are living hand-to-mouth in the way that I was when I was a young founder. And I contrast that with the experience of some of the people that I'm helping who are in the elite circles. And I just, it just is so unfair. I look at, say, I'm very proud of the work that we've been doing for the past seven years at the Harvard Social Innovation and Change Initiative, but each one of my students gets free money when they graduate because there was a philanthropist. And three of my students are from billionaire families. They really don't need the $20,000 to invest in whatever startup they started in class, but they get it anyway.  And so what I try to do is bridge the gap and create convenings where people who are extremely wealthy can actually meet people who they were never met, had it not been for us as the convener. And so putting people from different walks of life in the same room, so long as the objective is impact, economic mobility, and helping to democratize access to capital. And I found that just bringing people together makes such a difference because these people just never met because it seems as if they were living on different planets. And so that's why events like this are really important, but still you need an invitation to come to SoCAP, right? And so I feel like we just need to work more closely together to make sure that these exclusive networks are a little bit more accepting of people who don't have that pedigree. And somewhat permeable, because they're so rigid that it's really hard to break in. I think this next question is a good segue because it's also about access, and it's how do you get past some of the systemic barriers for diverse managers? For example, assets under management or track record of the management team, you know, sort of along the lines of how you allocate to emerging managers. I can take this one. Well, I'll tell you sort of some of the things that I think are interesting there, but so I think it's really hard. Like the up against a lot is, I think, applies to founders and to emerging managers. And the reality is like, you know, a lot of people will say to anyone who wants to go invest, like, just go start doing it. Just like, take a slice of your net worth and just go start investing. And like, that is a solution that is available to a very small percentage of people. And so there are ways to get creative, right? You can create your shadow portfolio, but all of that, it doesn't compare to the person who did have that wealth to just go say like, well, you know, I did all this angel investing and here's my track record. What's exciting to me is to see some seeds of new programs that are realizing just how high the barriers are to entry for diverse fund managers and trying to ease that just a bit. So first of all, I think there are funds like quads that are saying we are going to go out and find these people and not only fund them, but connect them to other fund managers and connect them to the establishment and like help build out that network and just give them exposure, like get their foot in the door and then it's up to them to go run with that. So that's really powerful because those fund to funds did not exist five years ago. And then there's also some interesting programs that are emerging that are realizing like from an economic perspective, it's really hard. So the way that a fund works is, you know, as a fund manager, you only start getting paid once you close your fund and you call capital and like, you know, people will say to emerging fund managers, prepare for a 24 month raise and say, okay, well, how do we make that math work? But there are new programs. I'll give a shout out to recast capital who just started this program with backing from, among others, Pivotal Ventures, which is Melinda French Gates's family office. And what they are doing is giving grants to female and diverse fund managers, $100,000 to start to be almost like that working capital, right?  And so all of that, they're not a lot of them. So I don't want to overstate how much is being done, but I'm excited to see those green shoots coming forward to support more managers because the reality is, if we think about how this all cascades, like when there is more capital in the hands of more diverse fund managers, that then trickles down to the founders that they back. And I think that's the way that we make change as a whole rather than relying on the same fundage managers to suddenly start changing how they're deploying their capital. I understand that, that's great. And I like that even though they're not a whole bunch, that you shared an example that you know of that can work. Okay, so this next question, I can't figure out if I like it because as a journalist I like to challenge people. Or... But I will allow anyone on the stage to answer, but how do you structure, hey, equity within your own organization? The question is essentially how do you walk your talk or as this person puts it, do you practice what you preach? Great question.  So we use, they have a whole algorithm that's all based on like data and like averages for your job title and all this stuff, but I do know that they are very aware of making sure that there's like no gender inequity in our organization. And the foundation strongly believes in paying people a thriving wage, not just a living wage. So I would say that we do get paid, do I make as much as I would if I worked in like private capital? No, of course not. But it's very meaningful and I feel like I'm paid very fairly. So we're a small team and the reality is like we're probably all underpaid because we're still building our firm. But I'll mention like we brought on an associate and we were intentional that we gave her Kerry in the fund, which at many funds associate level employees do not. And Claude, you had mentioned equity and I think equal pay is so important. But I think equity and ownership is what truly drives, what can be the solution to the wealth gap in this country. And so it was really important for us to make sure that our associate, even though we had no idea if she would work out, we have no idea if she would stay that like she had a path to ownership. And then this is something that we do talk to our underlying portfolio companies about a bit on the pay side, but for us, the walking of walk is like who are they hiring and are they then building diverse teams? And what we're saying is like it's the diversity that drives returns. How are we keeping them accountable to that and then also more importantly, supporting them and enabling them to build out a diverse team. Yeah, so in terms of practicing what we preach, I'm in the spirit of equity and I went the other way. And I have a chief investment officer who's also my business partner who actually makes 50% more than I do. And it's a woman who I recruited to be able to help me with the investment side of things. And where everyone's incentivized is only three of us really who are full-time employees at the fund but everybody has carry and everybody has upside. And so when interests are aligned around kind of long-term gains as opposed to instant gratification, it's a better outcome. For me, I'm much more interested in the long-term carry than I am in the salary that I'm getting now as a fund manager out of our management fees. But mind you, I already had an exit so I look at everybody's financial circumstances and calibrate that so that everybody could be happy. Because I find that when you underpay people or they're just not happy about their level of compensation, they get subpar performance. Thank you, that was honest and transparent. And I appreciate you guys. I want to know, do we have any more questions and could I get a time check? Are we good on time? So one of the things that I wanted to sort of popcorn in and ask you guys because I just think it might be valuable for people in the room is I think we learn as much from things that go well, as we do from things that don't go well. And I wonder if you could take a moment to share a valuable lesson that you've learned in the space of doing this work. It could be a recent lesson like last week or it could be a lesson that you learned several years ago or when you first got started. But what could you share that maybe somebody in the room can take away? I can perhaps start. So I'm very happy with the investments that we've made so far and we're looking really good certainly from the perspective of multiple and invested capital. But there's one investment that I'm really, really unhappy about because a lot of the work that we do is community building and what we call our social capital platform. We get people to share information, these convenings that I talked about, these summits that we organize, and so on. And one of the fund managers that we invested in actually started kind of bad-mouthing other people that we were looking to invest in and it clearly became a crabs and a barrel situation where one of the things, I really firmly believe that one of the things that I've held this back in the black community is this crabs and a barrel community because we feel often with that scarcity mindset that there's only very little capital around and that could be allocated so more for that person is less for me and I'm a believer that that rising tide will lift all boats and we've had this very frank conversation with that fund manager because it's totally against the spirit of what we are about which is we're all going to rise together and make money together as opposed to me, me, me, and more capital for me. You have a lesson learned, Casey? So many. I think, I don't know if this is so much relevant to this panel but don't fall into the idea, we have so many deals that come across our desks that it's urgent. This fund is closing in two weeks, this fund is closing in a month and I think the biggest lesson we ever learned was not putting one of our investments through full due diligence. We did a truncated due diligence, we put the investment, because it was like, oh, the impact and it's an important community member and we want to support this effort or whatever and that investment almost completely blew up and that would have been a lot of money that we weren't going to get back right there and then that sometimes you just have to say no and so we don't put anybody through speedy due diligence anymore, you have to go through the whole thing. Yeah, speedy and due diligence kind of thing. Even in news, it can get real dicey when you brush a thing. But also, I think especially in impact investing you're like, oh my gosh, I don't want to miss out on this opportunity to support this thing and there's so many emotions also tied up with impact investing and we forget that at the end of the day there's no mission without margin so you can't be like blowing a bunch of deals and that was the only time that's happened since I've been working there so we did get our money back so it worked out but we were like we were really fighting our nails for a little while. So I'll share a lesson and it's one that I I'm still sort of grappling with so I'll share it but it's a bit of an uncomfortable one because my instinct was different. The first version of our pitch was like really stark with the data and you know that just it was really like truly what was in our hearts and we kind of put it on the paper and we went out and we shared it with a bunch of people and we got pretty mixed feedback and what I realized is that the mixed part of the feedback was primarily from people who were part of the establishment and often it was like sort of an older white man who had been a venture capitalist for a while and we were saying like this system is broken and there's this whole part of the market that people are ignoring and the part that I wrestle with is like I don't feel like that's a fragile ego that I need to protect but the lesson was that what we realized was at this point in the game those are the people who are controlling the large sums of capital they are the people who we would like if our companies are going to go on and be those successful outlier companies they will likely need to get funding from one of those people and what we realized was that we had to build our fund in a way that was really true to us and our values and our founders and like authentic it didn't totally alienate some of the people that we needed to be successful and some of the people that were part of the establishment that were open to seeing this opportunity but like they needed to hear it in a way that they could receive it rather than being like well you're the problem and so that was an important lesson I still feel like I need to reinterpret that differently every day but I think the sort of summary is that we need to build in a way where our allies can really be part of it and can advocate for us and our portfolio companies and it can't just be women and people of color that we're turning to it needs to be in a way that a larger audience can hear that and get behind us to help her pull us forward yeah that's really good it can't just be the one it has to be the many we've got time for I think just one more but I'm gonna merge these last two in a way that I think might work so one of it is with all the talk of what might be some of the challenges around DEI people with deep pockets suing and things like that how can you work together in a strategic way to move forward to fight things like that and then as you close knowing things like that are going on there's lawsuits and all the hard work that goes into DEI what keeps you in the field what keeps you inspired do you want to speak to the lawsuit one more like the yeah I think I should speak to the lawsuit one because I'm directly impacted by that so I start there so I'm pretty sure most of you know about the lawsuit Edward Bloom brought against Fearless Fund which was one of the early funds that we invested in their base in Atlanta and so obviously that's been topic A since the summer certainly in our world because I mean this lawsuit could go all the way to the Supreme Court and could pretty much jeopardize a lot of the work that we do to invest in what I'll call again underrepresented founders and fund managers and so one of the lessons of that is if we all kind of bring together our collected networks and really support the fund managers at the center of this lawsuit then it doesn't really necessarily matter what the deep pockets are on the other side because the wisdom of crowds the collective intelligence could actually help to overcome this very serious challenge that the Fearless Fund is facing so the very fortunate thing about what's happening now is my business partner and mentor that I mentioned, Dick Parsons is part of an effort of people who are like him in the stratosphere to bring together a brain trust to be able to strategize around and pay legal fees on how to help the Fearless Fund because their success is our success and is everyone's success in this specific lawsuit so because it's so existential the fact that people are being mobilized by this threat is something that gives me a lot of hope because it could end up affecting many other industries and so the time for action is now and I'm really really proud that the people that I work with are actually taking a stand and also our front and center in this specific lawsuit yeah well thank you for the call to action I think sometimes situations like this they bring the right people into the room they galvanize yeah they do galvanize so with that said what's keeping you inspired you know what keeps you from running out the door what keeps you inspired in this space and staying with the work that you're doing honestly like and this is not just because we're on this stage together I'm not you know trying to flatter you or anything but I'm inspired by the conversation we had yesterday about life and family and success and what does it mean you know just sitting outside on the lawn that was a very inspiring thing for me I'm inspired by the conversations we've been having including on the podcast that you invited me to talking about how to build more equity and how to make sure that again justice belonging community is actually part of what we all aspire to as opposed to this kind of very very selfish mindset of trying to make money quickly for yourself and protecting that for your family and not really thinking of broader society so I'm really inspired by the people who are thinking of equity in the right way as opposed to what Tacoville described in his book Democracy in America which is Americans only care about their own backyard and their own money and their own bank account you know I feel like that's hopefully going to change in the future because there are people like the people in this room who actually care yeah that keeps you inspired well I was going to say it's I really do think it's like the people and this just this collective feeling of what we're doing is important it's not only a huge opportunity but it's important and it's interesting how many friends I have who maybe are at a more traditional fund or on Wall Street and they'll say what you're doing is it's like so interesting you must feel so good about it I'm like yeah I do and so it doesn't just feel like a job which it is but it's I'm so passionate about it and it feels like more of a calling and so that's what keeps me in when it's hard which it often is and I think on a day-to-day basis I find so much inspiration from our founders and who they are as people what they care about what they're building and like how I see them growing and achieving and shaping our future people often ask like how do you know when you're successful and they're all the metrics and all of those things but what the first thing I think of every time when someone asks that is we will be successful when the founders that we invest in are household names right when someone says they want to be a founder today they say you know I want to be Mark or Elon or Bill or you know when they say that they want when a child thinks about what they want to do and it's like I want to be a Julia or whoever that is when I will know that we are successful and that's what's so motivating to me I know we're out of time but I just want to on a closing note there are over 500 trillion dollars in institutional investment institution investments yeah like worldwide and when we look at what actually initiates change in our world what actually gets people elected to office what actually drives business decisions it is institutional investment dollars and so one of the things I'm really excited about our impact investing fund we said hey in addition to grant making can we make huge impacts in our community with these institutional dollars and the answers not only are we seeing huge impacts in the community through investing in local startups fund managers getting affordable housing units that we're investing in we are seeing a fantastic return we're seeing 18.8 percent five year annualized return in that portfolio so as we're seeing across the industry declines and pension fund returns in other large institutional returns because they are not creative they're not investing through the lens of diversity equity inclusion and they're creating barriers to do that we have a model that works and so I get up in the morning and I'm like how do we scale this bigger and we're working on ways to do that but it just it's so exciting to know that we can harness this 500 trillion dollars and actually put it to work directly in our communities and and I get to work on how do we make that playbook for everybody so it's very exciting thank you so much I just want to say thank you to all our panelists didn't I tell you guys they were brilliant thank you to you Ashley can I can I ask one thing I want to know what keeps you inspired oh good one all this I've been working and writing social issues for a long time criminal justice and health and education and immigration and politics that one almost took me out and it's just it's social change this has been phenomenal to be surrounded by people who wake up and they want to make a difference and they're not so deeply concerned that what I do isn't a silver bullet for the world but what I do makes a difference and as a journalist and an editor like that keeps me inspired stories keep me inspired and how people are responding to social issues and to inequities keeps me in the work yes thank you all


little off kilter okay okay right we're getting there yeah we'll get there um high school building committee dr. homo gave the report october 11th is the is the is the new turnover and our communication has gone out to the community and we'll be able to move at that point too administration it's going to be everything yeah everything yeah administration everything correct yeah okay because the discussion was is that we'd be delaying that wing uh a couple of weeks or something much the same way that the theater was they they changed no they changed they changed they originally going to do that and then they changed except yeah okay i just wanted yeah i just wanted to note that that was different so that we were all expecting to evacuate this building so it could be demolished on after we depart right and just to reiterate for parents who may be curious so because we had voted to delay the demolition of this building the students will have classrooms and places to be going to school full-time normal schedule until the building the new building is turned over uh liaison reports no liaison reports announcements no announcements future agenda items no future agenda items okay i have a motion to adjourn okay any second second okay are you gonna sound a doodle okay vote first okay so miss kettleson yes mr cardin yes yes yes yes yes okay i called out their names you didn't hear by said it okay thank you


Good afternoon, Zambia. I've been thinking about doing this and talking to you all. I have received so many messages from people to take courage, for me to take courage, for me to stand strong. And I'm so happy that you've considered how I feel about this. I only talk to you all about love, but before I do so, I would like to send a huge congratulation message to the president-elect. I do believe as the patriotic front, we put up a good fight. I do believe as the BND, the United Party for National Development, also puts up a good fight. We each had a role to play. And I truly believe that the will of God will prevail in our lives. We are one Zambia after all in one nation. It's very heartbreaking to be honest with you. But it's not the end of the road for us all as the patriotic front. I believe in our manifesto. I believe in our plans. The mandate is not ours anymore, of course. But I really wish the UPN did the very best. It breaks my heart to see all the violence that's happening, all the deaths. I pray every day for Zambia that gets united. I pray every day for Zambia that can show love and care to each other. Please, please, brothers and sisters, parents out there. Is this an earnest plea from me? Please stop the violence, please. There's no need for us to bring it all down just because you won, just because we didn't win. We're talking about real lives and real people. We have to move on as a country. We have to move on as a people of the soil, people of Zambia. What does Zambia represent? So, take courage. It's not an easy road. But this is not the way things should be. For our presidents, look at how they stood together yesterday to discuss the future of the nation. Please, brothers and sisters, take my plea, talk to someone, to talk to someone else. There's no point in all the harassment, everything that's happened. So, that said, I would like to thank my president, who I love so much on the very bottom of my heart. Thank you so much, Dr. Edgar Chagwa Lungu, you, sir, demonstrated a love for your people. For us, you did, you fought a good race, you fought a good fight. I'm very, very proud of you, sir. Thank you for adopting me on the patriotic front, the mighty patriotic front. Thank you so much, sir. So many people did not believe in me, but you believed in me. Thank you so much for trusting me with that position. The mandate of somebody else is right now, but I promise I'll try my level best to take care of the people of Mwanti, the best way that I can. My final sentiments to you, Zambia, is that changing government doesn't mean progress. Changing government means changing the way we're doing things currently. Let's forge ahead, let's develop our own industries, let's export. We are a beautiful country, and the sky is the limit for us. Thank you. Thank you for tuning in. I love you. I love Zambia. And may God be with us all. Bye.