With global corporate-venture-capital-backed (CVC) funding reaching $79 billion across 2,099 deals in the first half of 2,021 according to CB Insights, the chances are high that startups will find great opportunities with this growing investor set.
Entrepreneurs, however, are likely to discover that the investment process can be different for CVCs compared to private venture capital firms. While both types of investment firms tend to make decisions via an investment committee (IC), private VCs (inclusive of VCs with corporate backers that have an independent LPA structure) make up their ICs with firm partners and/or other venture-minded people.
But for CVCs investing off a corporate balance sheet, the IC can include corporate-minded people, such as the CEO or business unit leaders, who generally tend to be detached from the venture mindset and the requirements for operating in the VC world. As such, entrepreneurs will realize that a successful CVC investment decision tends to have different requirements compared to a private VC firm’s decision.
The volatile nature of space rocket engines means that many early prototypes end up embedded in dirt banks or decorating the tops of any trees that are unfortunate enough to neighbor testing sites. Unintended explosions are in fact so common that rocket scientists have come up with a euphemism for when it happens: rapid unscheduled disassembly, or RUD for short.
Every time a rocket engine blows up, the source of the failure needs to be found so that it can be fixed. A new and improved engine is then designed, manufactured, shipped to the test site and fired, and the cycle begins again — until the only disassembly taking place is of the slow, scheduled kind. Perfecting rocket engines in this way is one of the main sources of developmental delays in what is a rapidly expanding space industry.
Today, 3D printing technology, using heat-resistant metal alloys, is revolutionizing trial-and-error rocket development. Whole structures that would have previously required hundreds of distinct components can now be printed in a matter of days. This means you can expect to see many more rockets blowing into tiny pieces in the coming years, but the parts they’re actually made of are set to become larger and fewer as the private sector space race intensifies.
A ransomware gang called Vice Society claims it grabbed confidential data such as patient benefits, financial documents and lab results.
Another health care provider has apparently been the victim of a ransomware attack that exposed private patient information and other sensitive data. A ransomware group known as Vice Society has claimed responsibility for an August attack against United Health Centers that allegedly impacted all of its locations. The incident reportedly led to the theft of patient data and forced the organization to shut down its entire network, BleepingComputer reported on Friday.
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From ecosystem development to talent, much effort is still required for practical implementation of edge AI.
By Pushkar Apte and Tom Salmon
Rapid advances in artificial intelligence (AI) have made this technology important for many industries, including finance, energy, healthcare, and microelectronics. AI is driving a multi-trillion-dollar global market while helping to solve some tough societal problems such as tracking the current pandemic and predicting the severity of climate-driven events like hurricanes and wildfires.
What would a world without banks look like? The answer may lie in decentralized finance.
Decentralized finance is an emerging ecosystem of financial applications and protocols built on blockchain technology with programmable capabilities, such as ethereum and solana. The transactions get executed automatically through smart contracts on the blockchain, which includes the agreement of the deal.
“Anyone can actually build businesses on top of these protocols and using them the same way as we can today build an internet business on top of the HTTP IP protocol,” said Stani Kulechov, founder of a DeFi protocol called Aave.
Decentralized finance has captured only 5% of the crypto space, according to CoinGecko, but it has seen massive growth recently. There was $93 billion worth of DeFi assets in the crypto market as of June 2,021 up from $4 billion just three years ago. To be sure, DeFi’s growth has slowed since the summer of 2,020 and regulatory scrutiny from Capitol Hill has spiked over fears of crypto’s checkered past.
1:17-Chapter 1: The ABCs of DeFI 3:16-Chapter 2: The DeFi boom. 5:45-Chapter 3: Why people are excited about DeFi. 7:31-Chapter 4: What’s next?
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A study in which machine-learning models were trained to assess over 1 million companies has shown that artificial intelligence (AI) can accurately determine whether a startup ﬁrm will fail or become successful. The outcome is a tool, Venhound, that has the potential to help investors identify the next unicorn.
It is well known that around 90% of startups are unsuccessful: Between 10% and 22% fail within their ﬁrst year, and this presents a significant risk to venture capitalists and other investors in early-stage companies. In a bid to identify which companies are more likely to succeed, researchers have developed machine-learning models trained on the historical performance of over 1 million companies. Their results, published in KeAi’s The Journal of Finance and Data Science, show that these models can predict the outcome of a company with up to 90% accuracy. This means that potentially 9 out of 10 companies are correctly assessed.
“This research shows how ensembles of non-linear machine-learning models applied to big data have huge potential to map large feature sets to business outcomes, something that is unachievable with traditional linear regression models,” explains co-author Sanjiv Das, Professor of Finance and Data Science at Santa Clara University’s Leavey School of Business in the US.
It’s not just salespeople, traders, compliance professionals and people formatting pitchbooks who risk losing their banking jobs to technology. It turns out that private equity professionals do too. A new study by a professor at one of France’s top finance universities explains how.
Professor Thomas Åstebro at Paris-based HEC says private equity firms are using artificial intelligence (AI) to push the limits of human cognition and to support decision-making. Åstebro says t he sorts of people employed by private equity funds is changing as a result.
Åstebro looked at the use of AI systems across various private equity and venture capital firms. He found that funds that have embraced AI are using decision support systems (DSS) across the investment decision-making process, including to source potential targets for investments before rivals.