The Importance of Being Twitter
A reminder for new readers. That Was The Week collects the best writing on critical issues in tech, startups, and venture capital. I select the articles because they are of interest. The selections often include things I disagree with. The articles are only snippets. Click on the headline to go to the original. I express my point of view in the editorial and the weekly video.
Content this week from @sama, @geneteare,, @PackyMcCormick, @Bessemer, , @turnernovak, @Microsoft, @SoftBank, @ElonMusk, @TigerGlobalManagement, @MoonFire, @Anthropic, @MartinVarsavsky
Editorial - The Importance of Being Twitter
Sam Altman on GPT4 - 2-hour discussion with Lex Friedman
San Francisco is not the Zombie Apocalypse - Martin Varavsky
The Atlantic and the Washington Post both published pieces this week declaring that Twitter is a far-right social network.
A staff writer penned the Atlantic’s version. His opening paragraph is clearly not true, but like ChatGPT, he says it with authority:
“Twitter has long been described, even by its most ardent users, as a hellsite. But under Elon Musk, Twitter has evolved into a platform that is indistinguishable from the wastelands of alternative social-media sites such as Truth Social and Parler. It is now a right-wing social network.”
National columnist Phillip Bump wrote the Post’s piece.
He boldly claims that:
“By now it seems safe to conclude that Musk’s intent in buying Twitter was not only to dismantle an institution that he perceived as a tool that empowered the media but to transform the social media platform into a heavyweight in the right-wing ecosystem. If that’s the case, he has recently cemented two victories that bring that goal closer to reality.”
By guest hosting Ron DeSantis on Wednesday, a spectacular technical failure, the meme that Musk and Twitter are “right-wing” has deepened.
So what can we make of boldy-asserted mistruths written by journalists, not opinion pieces, in respected publications like The Atlantic and the Post?
My belief is that both are symbolic of society’s descent into anti-intellectual tribalism. Life has become a game of picking sides and caricaturing what one disagrees with, with the goal of marginalizing it to the point where its very existence is an affront to what is right. Where to say Twitter is to say “right-wing” and therefore beyond the pale. It is demonization.
Twitter is not a right-wing social network. Heck, Bernie Sanders is on it. And a zillion others. It is not a right-wing media venture. It is a perfectly fine place to publish and subscribe to various people, organizations, or persuasions. It really is a town square.
The critics are unhappy that actual right-wingers are allowed to be on the platform and, indeed, be high profile on it. It seems Twitter would only pass muster with them if such people were removed or constrained. Being present and challenged by others seems not enough to satisfy them.
And worse, they are leveraging publications like the Atlantic and the Post to proselytize their views. This seems like a “capture” to me in a tribal attempt to render the other tribe null and void.
This tribalism is not left-wing or right-wing. It is both. And it is shameful.
Another example of tribal thinking is the characterization of San Francisco as a nightmare city, pulled down by a left government intent on enabling criminals and the homeless to act beyond the law.
This week Martin Varsavsky, a very good entrepreneur of Argentinian descent, tweeted that his visit to San Francisco revealed it to not be in a zombie apocalypse. He revealed that this point of view was met with many replies calling him left-wing, just as Musk is being called right-wing. His tweet is this week’s tweet of the week.
What Musk and Varsavsky have in common is common sense and preparedness to question orthodox narratives with facts and opinions. Both are critical thinkers who experience repetitive name-calling as what it is, a shallow attempt to shut up anybody with whom one disagrees.
I was at my son’s Syracuse graduation last week and listened to former U.S. Secretary of Health and Human Services, Donna Shalala (a Lebanese American), talk about the need for critical thinking and questioning everything.
This is the opposite of the demand for repetitive orthodoxy called for by the Post and Atlantic. Twitter is a platform for everybody. That, it seems, is its crime. And that is why it is important for us to use it, be part of it, and embrace it. Leaving Twitter would be a victory for tribalism, which is not critical thinking. That is the importance of being Twitter.
To help remove the noise, I am publishing an hour-long interview Musk did yesterday with the Wall Street Journal. It is clear from the interview that any narrow political labeling of Misk is far from accurate and is itself open to being challenged as political. Andrew is still traveling, but normal videos will return next week.
Essays of the Week
Packy and Rahul Team Up to Cover the History and Future of Fusion
MAY 22, 2023
Packy McCormick x Rahul Rana
Two weeks ago, a startup funded and chaired by Sam Altman announced a big partnership with Microsoft. This time, instead of investing in Sam’s brain, Microsoft committed to buying his power.
Specifically, according to the press release:
Helion Energy (Helion) today announced an agreement to provide Microsoft electricity from its first fusion power plant. The plant is expected to be online by 2028 and will target power generation of 50 MW or greater after a 1-year ramp up period. The planned operational date for this first of its kind facility is significantly sooner than typical projections for deployment of commercial fusion power.
While Sam Altman selling to Microsoft invites obvious OpenAI comparisons, the better analogy may be to one of the companies founded by Sam’s erstwhile OpenAI co-founder: SpaceX.
Like SpaceX, Helion set an absurdly aggressive timeline in an industry not recently known for its speed. Like SpaceX, Helion is the beneficiary of billions of dollars and decades’ worth of government-funded research, of global competition and cooperation in the pursuit of civilization-scale goals.
And like SpaceX, Helion may mark a turning point in one of the coming decades’ most consequential industries, the baton handoff from the measured and fundamental world of government and academia into the chaos and haste of the market.
We’re using Helion liberally here. We don’t know who will win Fusion Race 2.0, and this isn’t a winner-take-all market. But Helion is a worthy stand-in for the growing number of privately funded fusion companies racing to bring the power of the stars to the earth’s electric grid, economically.
Imagine a bizarro relay marathon in which one runner carries the baton for the first 26.0 miles, opens up a backpack full of batons, and hands them out liberally to a waiting horde of sprinters to dash all-out for the final 0.2 miles. That’s the best analogy we can come up with for this moment in the Fusion Race.
Global governments are the marathon runner. From the race to develop thermonuclear weapons after World War II, to the $22 billion, 50+ year cooperative ITER reactor currently being built in France, to the National Ignition Facility’s ignition achievement in December 2022, governments have led fusion research efforts for the better part of eight decades.
May 22, 2023
Bessemer Venture Partners, one of the oldest and more established venture firms in the U.S., earlier this year said it was earmarking $1 billion of its most recent fund solely for investments in artificial intelligence.
The firm’s massive bet on the future potential for AI reflects its belief that the technology is a seismic shift that will fundamentally change the way billions of people work, said Sameer Dholakia, a partner on the firm’s growth team.
“Literally trillions of dollars of value gets created when you have these massive tectonic shifts,” Dholakia said in an interview.
“We’re creating an ecosystem around the entrepreneur and around our firm broadly, where we’re getting some of the best and brightest minds from generative AI to partner with us,” he said.
The billion-dollar AI commitment comes after Bessemer raised the largest fund in its history in September, seemingly in defiance of market conditions. This milestone announcement was made long after the private and public market slowed down, and the firm’s own cloud report charted what it refers to as the “SaaSacre” in software startups.
Shifts as consequential as the leaps in AI playing out now take place roughly once a decade, said Dholakia, who has spent 28 years in the software industry in various capacities.
Prior to joining Bessemer, he was the CEO of SendGrid, which he took public in 2017 before the company was acquired by Twilio in 2019 for $3 billion. He experienced the Netscape moment in 1995, the iPhone and AWS, and the cloud in 2006 to 2007.
But the AI transformation will play out in a very different way, contrasting with past technological leaps, Dholakia predicts
The “adoption curve on this one will be mind-blowingly fast,” he said, predicting that AI will be easier to adopt than previous platform shifts.
MAY 24, 2023
We collected 5,000 data points surveying emerging managers. Here are the results.
The entire tech ecosystem is adjusting to a new reality in 2023.
Dealmaking is down. The rate of investment activity on AngelList, a proxy for the broader market, was the lowest they’ve ever measured. VC-backed companies recorded only $5.8B in exits during Q1 this year, less than 1% of the exit value generated in 2021, building up pressure within the ecosystem.
As is VC fundraising. 2023 is on pace to have the lowest fundraising total since 2017. Things are especially difficult for emerging fund managers with commitments concentrated in larger-size vehicles. LPs are moving to risk-off in VC, passing on emerging managers in favor of established managers.
While there is credible data available on activity in the tech ecosystem overall (check out AngelList State of U.S. Early-Stage Venture: Q1 ‘23 report), there is a lack of data focused on the emerging fund manager experience. So, we crowdsourced input from the Signature Block audience.
Over 195 emerging managers* responded to our survey, resulting in over 5,000 data points on:
Backgrounds and experiences: Previous investing experience, operating experience, etc.
Fundraising: Target fund sizes, time to close, fundraising experience, etc.
Fund strategy: Investment focus, brand building, community approach, etc.
Market observations: Valuations, deal flow volume, overhyped and under-hyped spaces, etc.
If you only have a few minutes, here’s a summary of our key findings:
It’s a difficult time to raise a fund. 91% of fund managers reported that it was difficult or very difficult to close their fund with a majority raising for more than 6 months.
Most emerging managers are “breaking out” of existing firms, furthering the rise of the individual brand in VC. That said, solo GP funds are less common than it may seem.
There is increased specialization in venture with more emerging managers now identifying themselves as specialists than generalists.
While there has been an explosion of investment activity in AI/ML, emerging managers ranked it as the most overhyped space currently. They ranked longevity as the most under-hyped space.
*We qualify emerging managers as those raising or have closed their first or second fund.
Here are some of the most interesting findings from the emerging managers surveyed.
Background and experiences
63% are current or former founders.
Following the rise of operator angels, we’re seeing the rise of operator fund managers. Founding a company builds a network that unlocks access to deals and LP capital. It also provides unique perspective and credibility into specific domains that can help these managers see and win deals. This trend is also driven by infrastructure such as AngelList which makes starting and managing a venture fund more accessible and cheaper.
Note: Investors were able to select multiple options for this question.
73% are “breaking out” of existing VC firms.
The majority of emerging managers left another firm to start their own, furthering the rise of the individual brand in VC. Of those that “broke out”:
20.5% were a GP
16.9% were a partner (non-GP)
35.4% held a non-partner investing role
Investors were able to select multiple options for this question.
We specifically asked respondents not to include their current role in their responses.
91% found fundraising difficult or very difficult.
Fund managers are also feeling the effects of the generally depressed fundraising environment. But, most expected it. 73% of fund managers expected the level of difficulty they faced before they started raising.
32% decreased their target fund size.
This was lower than we expected considering how difficult it has become to raise from LPs. The majority are persisting with their fund size target and some even increased it.
85% took more than 6 months to close their recent funds. 52% took more than 12 months.
Signature Block just published its inaugural Q1 ‘23 report on the state of emerging managers, which are venture capital firms investing their first or second fund. The survey of 215 investors had lots of data around their experience, fundraising, investment strategy, and market observations.
If you’re into this, I recommend reading the full report here. Now on to the points that jumped out to me.
91% of emerging managers are finding fundraising difficult or very difficult
This tracks with what I’m seeing anecdotally. I shared this chart a few weeks ago on the current pace of fund closings based on Pitchbook data, which I think is deceptive:
A majority of the funds Pitchbook reports were closed in 2022 were mostly committed in 2021 and Q1 of 2022. Since then, the market has been almost completely frozen amongst some large institutional LP’s. Many of the new funds being announced recently (and showing up in the 2022 and 2023 data) were technically raised quite awhile ago. In fact, a common strategy for anyone raising capital is to announce the prior fundraising event when you start the next one…
If you look at startup exits (liquidity events), they’ve been practically non-existent for the past six quarters. These startups exiting and returning capital to VCs and their investors (LPs) is typically what funds the majority of capital being invested into the venture capital asset class. But who can blame them? Valuations are down significantly since 2021. It also means valuations are down in other asset classes, which institutional LPs will likely need to sell in to make new venture investments.
None of this bodes well for emerging managers. It’s the riskiest sub-asset class within venture capital, of which is one of the riskiest asset classes. This makes it very impacted during funding pullbacks.
by Oliver Hsu
Table of contents
The full-stack startup, as previously written about by our partner Chris Dixon, is an approach taken by some startups to bypass incumbents by building a complete, end-to-end product or service. This approach is in contrast to the traditional approach, in which startups aim to sell or license their technology to existing companies in their industry. We believe that there are tremendous opportunities in American Dynamism categories for these full-stack companies to be built; moreover, we think these companies can enable a thriving ecosystem of new technology companies to grow in industries that were previously more difficult for new entrants.
The prominent technology-first entrants in industries that contribute heavily to American resilience and dynamism often emerge first in the form of full-stack startups. Generally speaking, these industries include sectors where companies sell to government (like aerospace and defense) and provide citizen services in government-adjacent markets (like education or transportation), and in core domestic industries where government is a stakeholder (like logistics and industrials). In general, these companies own their distribution and relationship with the end customer, as well as vertically integrate more (though by no means all) of what goes into their product. In some ways, they run counter to the conventional wisdom that advises startups to narrow in on a core competency early, use it as a wedge with customers, and then expand from there.
Full-stack startups represent the beginning of a new chapter of technological acceleration in these industries. They function as the enablers of new startups in the industry, by creating new markets for suppliers and other services around them. These new startups do not have to be full stack, and can grow into massive businesses in their own right, because the full-stack companies and the markets they operate in grow so large that even adjacent markets represent massive opportunities.
Some prominent examples of full stack startups in these industries include:
SpaceX, which built launch vehicles themselves rather than serve as a point solution to NASA.
Tesla, which didn’t start out by selling batteries or electrification technology to existing auto OEMs. They built and sold cars — competing against the incumbent automakers.
Anduril, which focused on building products for defense with a vision to become the next prime, rather than start out as a supplier to the defense primes.
Flexport did not sell a software solution to freight forwarders — they became a software-powered freight forwarder themselves.
Lyft and Uber created parallel transportation systems instead of selling software to public transit, taxi, or private car services.
Zipline doesn’t sell delivery drones — it operates a logistics system.
The goal of this post is to outline a framework for thinking about full-stack startups — in a technology-agnostic way — as enablers of innovation in government-adjacent sectors, and how this might translate to other important yet technologically stagnant industries. To do this, we explore: (1) why markets in certain industries lend themselves well to full-stack startups; (2) how full-stack startups accelerate technology development and adoption in these industries; (3) some common characteristics of full-stack startups in these markets; (4) areas of opportunity; and (5) why these companies are still anomalies.
Why full-stack startups arise in certain industries
The full-stack startup can be seen as a reaction against the challenges of reform in stagnant industries. Marc Andreessen has spoken about the limits of institutional reform, where organizations — particularly large bureaucracies — are incapable of improvement via reform for a variety of reasons. Instead, Marc argues that progress in the domains occupied by these incumbents is achieved by building new institutions from scratch, and that the challengers starting these new things have outsized opportunity because incumbents won’t change. …
Video of the Week
AI of the Week
Does the acceleration in AI make your SaaS company more or less defensible?
Published in Point Nine Land
Last week, I looked into the question if AI is a platform shift as disruptive as the move from on-premise to the Cloud. My conclusion was that Generative AI is an asteroid impact event for B2B software, comparable to the launch of the iPhone or the Internet itself. But unlike most on-premise software companies in the 2000s, the SaaS leaders of today aren’t doomed. If they can adapt fast and embrace the shift towards much smarter B2B software, they are in a good position to survive and thrive.
A related question is whether the arrival of Generative AI, and the fact that it’s become 10x easier to build AI-powered software, is a net benefit for AI-first SaaS startups. If Google (or at least some people at Google) think, “We have no moat” (referring to open source competition to its LLMs), how can a startup use AI to become more defensible?
A few years ago, Louis wrote an excellent article titled Routes to Defensibility for your AI Startup. If you haven’t read it, stop reading this post and head over to Louis’ piece. :-) What I’d like to do is revisit the question in light of the latest advancements in AI, specifically GPT-4.
1) Not every AI feature will enlarge your moat (and it doesn’t have to)
Given how easy it’s become to add AI features like video transcription, text summarization, sentiment analysis, writing assistance, image generation, or data analysis, lots of companies will use general models like GPT-4 and a limited amount of fine-tuning to create real customer value. In these cases, adding AI will improve your product and make it stickier, but you’re not creating a deep moat, and that’s fine.
In these cases, companies will use LLMs just like other building blocks like open-source databases, file storage providers, and all kinds of open-source components or APIs. Using a MySQL database is not going to increase your defensibility, and neither is plugging in an AI API for, say, text summarization.
You should, of course, aim to build a product that is extremely hard to copy. But many AI features will be bricks in your fortress, not something that greatly expands your moat, and again, that’s OK.
Here’s how Morten Primdahl, co-founder & former CTO of Zendesk, put it in a recent conversation:
“For someone like me who prefers to build business logic, using GPT is no more of a moat than using MySQL is. I believe we’re witnessing the productisation of what we used to rely on lots and lots of hard earned ML efforts for, those teams will now n̶e̶e̶d̶ ̶t̶o̶ ̶r̶e̶i̶n̶v̶e̶n̶t̶ ̶t̶h̶e̶m̶s̶e̶l̶v̶e̶s be able to focus more on business specific needs.”
2) Creating deep moat from AI requires proprietary data
To create a substantial AI moat, you have to be in a situation where (a) you have access to proprietary data that is impossible to obtain for others and (b) that data leads to superior model performance. This is conventional wisdom, so I won’t elaborate much on this point. The reason why I’m mentioning it is that the bar for what is truly proprietary data has increased. GPT-4 has already been trained on an insanely large corpus of text documents, and OpenAI and its competitors will train future models on every potentially useful piece of text, video, or audio they can get hold of (plus potentially even larger amounts of synthetic data). This may include corpora of data that one would typically consider proprietary, such as a law firm’s legal agreements archive or decades’ worth of a hospital’s patient data. I’m not suggesting that e.g. OpenAI will do anything illegal. My thinking is that there’s a vast amount of data out there which doesn’t lose its usefulness for training if you remove personal information from it.
Rest of World spoke to the founder and CEO of OpenAI during his trip to Nigeria.
23 MAY 2023 • LAGOS, NIGERIA
AI models can be a force to reduce bias, not reinforce it, Sam Altman says
Last week, Sam Altman, the founder and CEO of OpenAI, spoke at an event in Lagos, Nigeria. During his trip, he met with members of the tech community and talked about the prospects for artificial intelligence. Rest of World spoke to Altman after the event. This interview has been edited for clarity and length.
You talked about the potential of Africa’s youth population. What’s the best way to think about this potential in terms of production?
When a new technological revolution comes along, many people pay attention and say we can now build amazing new tools. It happened with computers, happened with the internet, and happened many times before. What I think is going to happen — and certainly what I got to see some of today — is people are going to form new startups, or they’re going to pivot existing startups and say, “I’m going to build something that is either better than what I could build before or is brand-new, something I just couldn’t build before at all.” And the energy here seems great for that. People are pushing the limits of technology and coming up with new ideas we haven’t heard before.
What are you most excited about in terms of AI’s potential for innovation or solving problems in Africa?
I’ve gotten to talk to many startups today that are doing different things, and they all sound amazing. It seems like people building startups here are convinced that they will generally have a very positive impact on Africa. They said it is the most excited they’ve been about any new technology in a long time.
How can we address the issues of bias, fairness, and often racist tendencies in generative AI systems, and what role do you think regulation can play in ensuring equitable outcomes?
We have a technology called RLHF [reinforcement learning from human feedback] that is good at reducing bias in these systems. A paper I saw last week found that by using RLHF on these models, you could make a model with much less implicit bias than humans. I’m optimistic that we will get to a world where these models can be a force to reduce bias in society, not reinforce it. Even though the early systems before people figured out these techniques certainly reinforced bias, I think we can now explain that we want a model to be unbiased, and it’s pretty good at that.
Image Credits: TechCrunch
Microsoft wants to take the pain out of designing web pages. AI is its solution.
Today marks the launch of Copilot in Power Pages in preview for U.S. customers, an AI-powered assistant for Microsoft’s low-code business website creation tool, Power Pages. Given prompts, Copilot can generate text, forms, chatbots and web page layouts as well as create and edit image and site design themes.
To create a form, for example, users can simply describe the kind of form that they need and Copilot will build it and auto-generate the necessary back-end database tables. Those tables can then be edited, added to or removed using natural language within Copilot.
“As the maker, you describe what you need in natural language and use Copilot suggestions to design web pages, create content and build complex business data forms for your website,” Sangya Singh, VP of Power Pages at Microsoft, told TechCrunch in an email interview. “You no longer need to start from a blank slate.”
Generating a website with AI isn’t exactly a novel idea — not in this day and age, at least. Tools like Jasper can handle copy, images, layouts and more, while generators like Mixo can create basic splash pages when given a short description.
Image Credits: Billy H.C. Kwok / Bloomberg (opens in a new window)/ Getty Images
Microsoft wants companies to build their own AI-powered “copilots” — using tools on Azure and machine learning models from its close partner OpenAI, of course.
Today at its annual Build conference, Microsoft launched Azure AI Studio, a new capability within the Azure OpenAI Servicethat lets customers combine a model like OpenAI’s ChatGPT or GPT-4 with their own data — whether text or images — and build a chat assistant or another type of app that “reasons over” the private data. (Recall that Azure OpenAI Service is Microsoft’s fully managed, enterprise-focused product designed to give businesses access to AI lab OpenAI’s technologies with added governance features.)
Microsoft defines a “copilot” as a chatbot app that uses AI, typically text-generating or image-generating AI, to assist with tasks like writing a sales pitch or generating images for a presentation. The company has created several such apps, such as Bing Chat. But its AI-powered copilots can’t necessarily draw on a company’s proprietary data to perform tasks — unlike copilots created through Azure AI Studio.
“In our Azure AI Studio, we’re making it easy for developers to ground Azure OpenAI Service models on their data … and do that securely without seeing that data or having to train a model on the data.” John Montgomery, Microsoft’s CVP of AI platform, told TechCrunch via email. “It’s a tremendous accelerant for our customers to be able to build their own copilots.”
News Of the Week
May 22, 20239:19 PM PDT
May 22 (Reuters) - SoftBank Investment Advisers, which manages two Vision Funds, is exploring launching a private credit strategy that provides debt or debt-like structured financing for late-stage tech startups, people familiar with the matter told Reuters.
The fund aims to offer liquidity options to tech startups, including some of SoftBank's own portfolios, amid a slow venture funding environment and a weak market for IPO exits. It targets returns in the mid-teens, one of the sources added.
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The plan, which was still in its early stage and could change, was first reported by Bloomberg News earlier on Monday. SoftBank declined a Reuters request to comment.
The elusive unicorn is no longer a myth in the U.S. startup world, with over a thousand private startups reaching a $1 billion valuation in the last 25 years.
While some of these startups eventually go public and go on to become household names, it’s also common for founders to exit through mergers and acquisitions (M&A), by selling their startup to another organization. In fact, over half of the 1,110 unicorns in the U.S. have made some sort of an exit—either through an IPO, a direct listing, a SPAC or an acquisition—since 1997.
Ilya Strebulaev, professor of finance and private equity at the Stanford Graduate School of Business, brings us this visualization featuring the companies that acquired the most unicorns over the last 25 years.
Strebulaev’s database lists 137 private and public companies along with PE firms who’ve acquired at least one unicorn since 1997, totaling 177 acquisitions.
The Biggest U.S. Unicorn Acquirers
In total, 27 companies have acquired two or more unicorns, accounting for nearly 38% of all acquisitions. 110 companies have acquired just one unicorn.
Meta, the parent company of Facebook, leads the pack with the most unicorn acquisitions in the U.S., purchasing five unicorns since its founding in 2008, including: Kustomer, WhatsApp, Instagram, CTRL-Labs, and Oculus VR.
Notably, WhatsApp—which closed at a purchase price of $19 billion—was Meta’s most expensive acquisition yet, over nine times their next most expensive purchase, Oculus VR.
Meanwhile, Alphabet (now the parent company of Google) and Cisco are tied in second place with four U.S. unicorn acquisitions each.
Alphabet: YouTube, Actifio, Nest Labs, Looker Data Sciences
Cisco: Cerent, Duo Security, AppDynamics, Jasper
Unlike its Big Tech peers, Apple has only made the one U.S. unicorn acquisition: navigation company HopStop that helped bring public transit features to Apple Maps.
Meanwhile, 56% of acquirers received venture capital funding of their own when they were private companies. This includes pack leaders like Meta, Cisco, Alphabet, and Amazon.
May 19, 2023
After a yearslong buying spree in the VC market, Tiger Global has been playing the role of seller in recent months.
The New York-based crossover investor has hired Evercore to shop a so-called strip sale in the secondary market to liquidate a curated portfolio of mid- and late-stage VC-backed companies, according to a person with direct knowledge of the sale and two others who have been briefed on the deal.
The firm hopes to sell interests in its private holdings to return some liquidity to LPs, as first reported by the Financial Times earlier this week. The role of Evercore, a leading secondaries adviser, and the structure of the planned sale were previously unreported.
Evercore didn't respond to a request for comment. Tiger Global declined to comment.
GP-led strip sales are relatively common in private equity but are less common in venture capital. The strategy will allow Tiger to generate liquidity for its LPs at a time when its tech holdings cannot be exited through IPOs or M&A deals. In these kinds of sales, GPs sell a portion or a percentage of underlying assets while still retaining some future upside in the remaining stakes.
A few months ago, Tiger put together a large basket of assets and tested the market by asking buyers to submit bids, the person with direct knowledge of the sale said. A lead buyer didn't immediately emerge, likely due to a large bid-ask spread that investors are observing in the secondary VC market.
Tiger, which manages more than $50 billion, is marketing assets worth hundreds of millions of dollars. The structure and size of the transaction may still change depending on buyer interest.
The deal will likely go through several iterations and adjustments, both to the mix of assets and the price, one of the people said. The ultimate assets will likely include stakes in companies from across several funds, the person added.
Tiger has accumulated stakes in some of the biggest names in VC, leading mega-rounds for Revolut, Getir and Brex.
Published May 19, 2023
By Andrew Hutchinson, Content and Social Media Manager
As you can see in these images, shared by ICYMI’s Lia Haberman, the new app is essentially a simplified version of Twitter, more aligned with a chat-based feed.
That’s deliberate, because over the last few years, more conversation on IG has switched to DMs, with the main feed becoming a discovery platform, as users move away from public posting activity.
With this in mind, the new, separate app is designed to be like a giant group chat that anybody can join – which is similar to Twitter, in concept, but with a more Instagram-specific tilt.
In terms of specifics, users will be able to sign onto the app using their Instagram credentials, including their username, while also being able to sync up their IG followers. Users will be able to post text updates of up to 500 characters and able to add links, photos, and videos up to 5 minutes in length.
But there seems to be something missing.
MAY 23, 2023 3:53 PM EDT
Elon Musk continues to preach that his acquisition of Twitter has been positive for the social media outlet.
Musk on Tuesday tweeted that the social media platform has improved in terms of the content posted.
“Both quality & quantity of high quality posts of all kinds (short text, long essays, pictures, audio & video) have improved dramatically,” Musk said in a tweet.
Twitter has made many changes since Musk took over in late October. Some of the changes include Twitter Blue and the infamous blue check verification that now charges users $8 per month, the reinstatement of previously banned accounts like Donald Trump, and the ability to tweet longer text and video posts.
Musk believed that the previous Twitter had begun to hinder free speech with its verification systems and other methods, and his moves on the platform have trended toward what he believes to provide that freedom. His latest tweet connotes that Twitter, which he referred to as “humanity’s digital public square,” is trending toward the direction he envisioned
Image Credits: GREGG NEWTON/AFP/Getty Images
It was back in the pandemic era of 2021 that we reported on the launch of Moonfire, at the time a $60 million “Fund I” seed-stage “data-driven” VC geared around the new world of remote working and remote pitching.
Its new $115 million fund-raise (“Fund II”) plans to continue what it calls its “data-driven” approach.
Since its launch by former Atomico co-founder Mattias Ljungman, Moonfire says it has built-out custom AI models and a tech stack to hunt down new prospective startups.
It now claims, in a statement, to review “up to 50,000 companies every week” (although this claim has not been independently verified by TechCrunch).
That said, it claims, for instance, to have discovered U.K. fintech LiveFlow via its AI engine, going on to lead the pre-seed round alongside Seedcamp.
The fund says it is looking at companies in AI, web3 and AR/VR, as well as health, work, finance and gaming.
Image Credits: Mike Windle / Getty Images
Disney is actively preparing to launch a standalone ESPN streaming service, according to a new report from The Wall Street Journal. The report indicates that ESPN is planning to sell its channel directly to cable cord-cutters as a subscription-streaming service in the coming years. It’s unknown when Disney plans to launch the service.
The report comes as Disney and ESPN have previously said that the channel would eventually be available as a standalone streaming service. The companies are now reportedly setting this plan into motion with a new project internally codenamed “Flagship.” ESPN has started to secure flexibility in its deals with cable providers and is having similar discussions with pro sports leagues.
Disney will reportedly continue to offer EPSN as a TV channel even after breaking it out into its own streaming service. Still, the shift will have significant implications for cable TV providers, given that live sports on ESPN are one of biggest draws of traditional cable. The providers, who pay to carry the ESPN channel, would end up having to compete with the new streaming service.
Although the sports media giant already has a monthly streaming service called ESPN+, the service doesn’t offer access to the ESPN channel itself. It includes live programming of certain MLB and professional hockey games. The service notably does not include NBA and NFL telecasts, which are currently only available on TV. With this new streaming service, ESPN plans to fully transition to streaming.
Disney did not respond to TechCrunch’s request for comment.
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May 23, 2023 7:30 AM
Image Credit: Anthropic
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Anthropic, a San Francisco-based AI startup and rival to OpenAI, announced today that it has raised $450 million in Series C funding led by Spark Capital, a venture capital firm that has backed companies like Twitter, Slack and Coinbase. The round also included investments from Google, Salesforce Ventures, Sound Ventures, Zoom Ventures, Menlo Ventures, and others.
Founded by former employees of OpenAI, Anthropic will use the new financing to expand its product offerings, scale its AI assistant Claude and conduct research on ways to ensure AI systems behave ethically and avoid potential harms. Anthropic was founded in 2021 to focus on these issues and has become a leader in AI safety research.
Claude, the company’s flagship product, is based on Anthropic’s research into training helpful, honest and harmless AI systems. The company says that Claude is designed to provide reliable AI services that can positively impact businesses and consumers now and in the future. Claude is also more transparent about its behaviors and limitations than other AI systems such as ChatGPT, and can handle adversarial conversations and follow precise instructions.