Tools for your investor soul

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I. Setting the stage

As everything these days seems to move online, it may be a good moment also for investors to sit back and re-evaluate the ways they run their businesses.

When I started this mapping (and yes, it was way before the lockdown), my main goal was to simply understand what was the current landscape of tools that investors could leverage and how to choose the best ones that could fit specific needs and structures.

I was also a bit skeptical and, let’s say that, a bit fed up with the overused adoption pattern of “everyone else is using it”, and I had to look with my own eyes to the different possibilities. …


Is AI making more good than harm?

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I. Is AI doing any good at all?

Researchers, entrepreneurs, and policy-makers are increasingly using AI to tackle development challenges. In other words, using AI for a greater good is a real thing.

Several studies and prototypes have been run to prove the value of AI in high-impact fields such as healthcare (Chunara et al., 2012; Caicedo-Torres et al., 2016; Pathak and Kumar 2016; Robertson and DeHart 2010; Waidyanatha et al., 2013) or environmental issues (Tehrany et al., 2014; Ferris, 2010; Tien Bui et al., 2012; Kapoor et al., 2010). …


Assessing different ML methods to better score startups

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Credit: https://bit.ly/2lKcSPc

Download the full article: https://ieeexplore.ieee.org/document/8821312

I. Setting the stage

If you have read some of my previous posts, you may know I am very bullish on data-driven funds. The rationale for my optimism is that I fundamentally believe that machine learning can bridge the asymmetric information gap between founders and investors, making both of their lives better and easier.

As part of my work and effort to try to advance the field a bit, I have been doing research on how AI has already been used in VC, but I also wanted to play with data and the following results are the first attempt to do so. …


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https://tnw.to/77lFu

Being a good investor is, first of all, a matter of discipline.

It is obvious that most of the time being a thematic-driven or general investor gives you more flexibility on where to invest, but it also makes easier for you to get lost into any opportunity that may knock on your door. Shaping an investment thesis instead helps you finding a rationale and restricts your playground in such a way that you cannot forget what it is relevant to you.

A thesis is always there to remind you why you invest in what you invest, why exactly you are in the game and what your inner investment boundaries are. …


Rewriting Human Life in the Digital Age

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I. Setting the stage

Healthcare is a rare bird. We can neither disregard it nor make it cheap, simple, and safe (Fernandez et al., 2012). In fact, we globally spend more than 10% of the GDP in healthcare and about $1,000 per capita every year (World Health Organization, 2018). But this is not the whole story: approved drugs halve every 9 years (i.e., …


Who is using AI to be a better (and smarter) investor

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I. A data-driven what??

The ones of you who know me are very well aware that if there is something which has sort of obsessed me for the last few years, this is definitely how to use analytics and AI to improve the venture industry.

While I tended to focus on scouting and evaluation, I learned that AI can be also used to spot general trends, identify market gaps, improve VCs portfolio management, better match co-investors, and deals, gather intelligence on competitors’ landscape, identifying potential acquirers, and improve pricing models.

I have been thinking about those issues for a while now (and stay tuned because I will post over the next few months my latest research in this field), and did already write on the importance of using AI in VC, summarized some academic research on this topic, and generally wrote about AI investors and accelerators. …


A primer on Multi-Agent Systems, Agent-Based Modeling, and Swarm Intelligence

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Image Credit: Joachim Wendler/Shutterstock

I. Setting the stage

Almost two years ago, I paused thinking about the future of AI and drew down some “predictions” about where I thought the field was going.

One of those forecasts concerned reaching a general intelligence in several years, not through a super powerful 100-layers deep learning algorithm, but rather through something called collective intelligence. However, except for very obvious applications (e.g., drones), I have not read or seen any big development in the field and I thus thought to dig a bit into that to check what is currently going on.

As part of the AI Knowledge Map then, I will have a look here not only at Swarm Intelligence (SI) but more generally at Distributed AI, which also includes Agent-Based Modeling (ABM) and Multi-Agent Systems (MAS). …


The convergence of AI, blockchain, and IoT

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Image Credit: Pixbay

The 21st century would be the “century of complexity” (Stephen Hawking)

I. Setting the stage

The IoT and consumer hardware industry have seen multiple failures and a few exits over the last 12–18 months (while the B2B side has been doing a bit better overall) and some critics have been recently made to the industry to slow down.

In spite though of the current pushback, the sector is still increasing and attracting capital and talents. Clearly, there are multiple reasons on why this is the case, but I firmly believe that one of those is the convergence of IoT and Artificial Intelligence with the Blockchain as the infrastructural backbone, which is unlocking the next step not only on the tech-side but also on the business one. …


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A few weeks ago I wrote a quite long post trying to highlight the existing studies that either proved or disproved the impact of a specific feature on the probability of a company to succeed.

The post is very detailed and frankly sometimes hard to read cause it looks more like an academic literature review than an accessible blog post that you can read on your way to work.

So I thought to summarize the findings of that article in a table, which shows the variables (and the respective reference studies) having either a direct impact on the success’ likelihood of a company, or an indirect impact through a higher probability of being funded or getting a higher valuation, plus features that are known in the industry and proved by industry players (where I cannot verify the rigor of the analysis). …


A sketch of a new AI technology landscape

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A shorter version of this article appeared first on Forbes

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The article has also been awarded with the Silver badge by KDnuggets as one of the most read and shared in August 2018.

I. Introductory thoughts

I have been in the space of artificial intelligence for a while, and I am aware that multiple classifications, distinctions, landscapes, and infographics exist to represent and track the different ways to think about AI. …

About

Francesco Corea

Research Lead @Balderton. Formerly @Anthemis @UCLA. All opinions are my own.

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