That Was The Week is an editorialized and curated weekly look at developments in tech, startups, and venture investing with a video and podcast for paid subscribers. All free subscribers get a 6-month complementary paid subscription.
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Disrupt Edition
Sunday, November 3, 2024 • Duration 32:37
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Irrational Liability
Saturday, August 31, 2024 • Duration 39:05
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Kids Love AI
Friday, August 23, 2024 • Duration 38:18
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Is Europe Dying?
Saturday, August 17, 2024 • Duration 36:19
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A Midsummer Night's Dream
Saturday, July 27, 2024 • Duration 36:50
I am still on my summer hiatus, but Andrew’s travel was postponed, and he wanted to do a show. So here it is, video only. Enjoy, and see you on August 16th.
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Rise of The Algorithms
Sunday, July 7, 2024 • Duration 37:58
Hat Tip to this week’s creators: @jaredheyman, @PeterJ_Walker, @cartaInc, @Om, @davemcclure, @vntrcapital, @mgsiegler, @sarahfielding_, @elevenlabsio, @fredwilson, @markgurman, @e_howcroft, @UtkarshShetti, @steph_palazzolo, @runwayml, @EricHSchwartz, @Cloudflare
Contents
Editorial: Rise of the Algorithms: Private Markets Indexing is Coming.
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Is There an AI Bubble?
Sunday, June 30, 2024 • Duration 33:35
Hat Tip to this week’s creators: @PeterJ_Walker, @mgsiegler, @jglasner, @lennysan, @AndreRetterath, @alex, @pmarca, @nklsrh, @dmehro, @timmarchman, @adamclarkestes, @Kyle_L_Wiggers, @MTemkiContents
It’s Sunday, two days later than I usually send this out. Two excuses. I was in recovery from PTSD after the “debate.” And then I almost had a relapse watching England in the Euro last 16 game against Slovakia.
I’m unsure of my mental state now (we won 2-1 in extra time). But the other, more important “game” is still undecided.
But in AI, it seems everybody is getting PTSD from wild allegations that AI might kill the human race to now new suggestions that there may be a bubble in valuations for early-stage companies.
The items in this week’s newsletter are really good. MG Seigler, Alex Wilhelm and Peter Walker dominate. The first two are former TechCrunch writers (hats off to Mike Arrington for his talent-spotting). Peter is the leading contributor to VC data; he has access to Carta data and uses it super effectively.
MG and Alex have relatively new newsletter sites - SpyGlass and Cautious Optimism, respectively). They are great observers and even better writers - subscribe. Links in their articles are below.
Microsoft really s**t the bed here both from a security and PR perspective. And what's left sounds very 'meh'. It's almost like Microsoft forget the 'Copilot' part of 'Copilot+ PCs'. And certainly they forgot the '+' part.
MG also wrote about the EU and Apple, claiming that the EU is seeking to entrap Apple by refusing to state what Apple can and cannot do with its AI intentions. Apple, in response, is saying it will not launch AI in Europe until the EU says what product flexibility it has.You have to smile. Apple plays this game super well.Finally, he has ‘Behold the Hackquisition’, which shows how big tech avoids M&A blocks by buying teams instead of companies.
Alex Wilhelm’s anticipation of the Circle (USDC) IPO is a great example of his regular style and substance.
Peter Walker heads up data storytelling at Carta (great title). This week, he also has three pieces, all originally posted on his LinkedIn profile.
‘Is there an AI bubble’ (my title) examines the spread of Series A venture funding valuations. He separates the percentiles and measures the spread between them, noting that the gap between the 50th percentile and the 95th is the widest ever - even wider than 2021 and 2022. This is for SaaS rounds that include much AI.
In H1 2019, the 50th percentile for pre-money valuations was $26M (Series A SaaS companies only, primary rounds). The 95th pct at that time was $96M.Now that's a pretty large gap. We're talking a 3.7x jump from the middle to the top end.But today things are even more skewed.𝗦𝗲𝗿𝗶𝗲𝘀 𝗔 𝗦𝗮𝗮𝘀 𝗩𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻𝘀 𝗶𝗻 𝗛𝟭 𝟮𝟬𝟮𝟰• 50th pct: $44M• 95th pct: $203M• Gap: ~4.6xThat 4.6x gap is the largest of the past 5 years and likely the past 10, though I don't have full data to prove it.
Regular readers will know my point of view. Yes, there is a bubble in that smart money wants to be in the best AI companies and will compete on price to secure equity. And no, there is no bubble because this chase for future-winning companies is entirely rational. At a time when the entire planet is about to become AI users - even without being aware of it - enormous value will be created. The price of current participation is far below the actual value that will ultimately be created.
I had not heard of Leopold Aschenbrenner until yesterday. I was meeting with Faraj Aalaei (a SignalRank board member) and my colleague Rob Hodgkinson when they began to talk about “Situational Awareness,” his essay on the future of AGI, and its likely speed of emergence.
So I had to read it, and it is this week’s essay of the week. He starts his 165-page epic with:
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them.
So, Leopold is not humble. He finds himself “among” the few people with situational awareness.
As a person prone to bigging up myself, I am not one to prematurely judge somebody’s view of self. So, I read all 165 pages.
He makes one point. The growth of AI capability is accelerating. More is being done at a lower cost, and the trend will continue to be super-intelligence by 2027. At that point, billions of skilled bots will solve problems at a rate we cannot imagine. And they will work together, with little human input, to do so.
His case is developed using linear progression from current developments. According to Leopold, all you have to believe in is straight lines.
He also has a secondary narrative related to safety, particularly the safety of models and their weightings (how they achieve their results).
By safety, he does not mean the models will do bad things. He means that third parties, namely China, can steal the weightings and reproduce the results. He focuses on the poor security surrounding models as the problem. And he deems governments unaware of the dangers.
Although German-born, he argues in favor of the US-led effort to see AGI as a weapon to defeat China and threatens dire consequences if it does not. He sees the “free world” as in danger unless it stops others from gaining the sophistication he predicts in the time he predicts.
At that point, I felt I was reading a manifesto for World War Three.
But as I see it, the smartest people in the space have converged on a different perspective, a third way, one I will dub AGI Realism. The core tenets are simple:
* Superintelligence is a matter of national security. We are rapidly building machines smarter than the smartest humans. This is not another cool Silicon Valley boom; this isn’t some random community of coders writing an innocent open source software package; this isn’t fun and games. Superintelligence is going to be wild; it will be the most powerful weapon mankind has ever built. And for any of us involved, it’ll be the most important thing we ever do.
* America must lead. The torch of liberty will not survive Xi getting AGI first. (And, realistically, American leadership is the only path to safe AGI, too.) That means we can’t simply “pause”; it means we need to rapidly scale up US power production to build the AGI clusters in the US. But it also means amateur startup security delivering the nuclear secrets to the CCP won’t cut it anymore, and it means the core AGI infrastructure must be controlled by America, not some dictator in the Middle East. American AI labs must put the national interest first.
* We need to not screw it up. Recognizing the power of superintelligence also means recognizing its peril. There are very real safety risks; very real risks this all goes awry—whether it be because mankind uses the destructive power brought forth for our mutual annihilation, or because, yes, the alien species we’re summoning is one we cannot yet fully control. These are manageable—but improvising won’t cut it. Navigating these perils will require good people bringing a level of seriousness to the table that has not yet been offered.
As the acceleration intensifies, I only expect the discourse to get more shrill. But my greatest hope is that there will be those who feel the weight of what is coming, and take it as a solemn call to duty.
I persisted in reading it, and I think you should, too—not for the war-mongering element but for the core acceleration thesis.
My two cents: Leopold underestimates AI's impact in the long run and overestimates it in the short term, but he is directionally correct.
Anthropic released v3.5 of Claude.ai today. It is far faster than the impressive 3.0 version (released a few months ago) and costs a fraction to train and run. it is also more capable. It accepts text and images and has a new feature that allows it to run code, edit documents, and preview designs called ‘Artifacts.’
Claude 3.5 Opus is probably not far away.
Situational Awareness projects trends like this into the near future, and his views are extrapolated from that perspective.
Contrast that paper with “ChatGPT is B******t,” a paper coming out of Glasgow University in the UK. The three authors contest the accusation that ChatGPT hallucinates or lies. They claim that because it is a probabilistic word finder, it spouts b******t. It can be right, and it can be wrong, but it does not know the difference. It’s a bullshitter.
Hilariously, they define three types of BS:
B******t (general)
Any utterance produced where a speaker has indifference towards the truth of the utterance.
Hard b******t
B******t produced with the intention to mislead the audience about the utterer’s agenda.
Soft b******t
B******t produced without the intention to mislead the hearer regarding the utterer’s agenda.
They then conclude:
With this distinction in hand, we’re now in a position to consider a worry of the following sort: Is ChatGPT hard b**********g, soft b**********g, or neither? We will argue, first, that ChatGPT, and other LLMs, are clearly soft b**********g. However, the question of whether these chatbots are hard b**********g is a trickier one, and depends on a number of complex questions concerning whether ChatGPT can be ascribed intentions.
This is closer to Gary Marcus's point of view in his ‘AGI by 2027?’ response to Leopold. It is also below.
I think the reality is somewhere between Leopold and Marcus. AI is capable of surprising things, given that it is only a probabilistic word-finder. And its ability to do so is becoming cheaper and faster. The number of times it is useful easily outweighs, for me, the times it is not. Most importantly, AI agents will work together to improve each other and learn faster.
However, Gary Marcus is right that reasoning and other essential decision-making characteristics are not logically derived from an LLM approach to knowledge. So, without additional or perhaps different elements, there will be limits to where it can go. Gary probably underestimates what CAN be achieved with LLMs (indeed, who would have thought they could do what they already do). And Leopold probably overestimates the lack of a ceiling in what they will do and how fast that will happen.
It will be fascinating to watch. I, for one, have no idea what to expect except the unexpected. OpenAI Founder Illya Sutskever weighed in, too, with a new AI startup called Safe Superintelligence Inc. (SSI). The most important word here is superintelligence, the same word Leopold used. The next phase is focused on higher-than-human intelligence, which can be reproduced billions of times to create scaled Superintelligence.The Expanding Universe of Generative Models piece below places smart people in the room to discuss these developments. Yann LeCun, Nicholas Thompson, Kai-Fu Lee, Daphne Koller, Andrew Ng, and Aidan Gomez are participants.
Checkmate! That seems like the appropriate word if you analyze what happened with OpenAI this week.
After being built into every conceivable Microsft interface, Apple announced that it would integrate OpenAI into all of its operating systems across devices via Siri.
By locking up Microsoft and Apple, it has effectively locked out Google, at least for now. That will leave Google itself as the only large implementation of its Gemini AI family.
This gives Apple a global advantage in the iPhone versus Android battle. Few will prefer Gemini to OpenAI.
Beyond that, Apple successfully showed how its own ‘Apple Intelligence’ will face inwards to the device, interoperating with all apps and supporting ‘actions’ while leaving all user data on the device. And when you need more power than the device can deliver, the new Apple Intelligence Cloud steps up in a fully encrypted secure environment. Even Apple cannot decrypt your data as it has no keys.
Ben Thompson from Stratechery sums up Apple’s play as follows:
This is good news for Apple in two respects. First, with regards to the title of this Article, the fact it is possible to be too early with AI features, as Microsoft seemed to be in this case, implies that not having AI features does not mean you are too late. Yes, AI features could differentiate an existing platform, but they could also diminish it. Second, Apple’s orientation towards prioritizing users over developers aligns nicely with its brand promise of privacy and security: Apple would prefer to deliver new features in an integrated fashion as a matter of course; making AI not just compelling but societally acceptable may require exactly that, which means that Apple is arriving on the AI scene just in time.
The concept of “just in time” seems appropriate. Although, as a developer possessing all of the beta products, I can say that very few of the features announced are yet available.
The contrast with Microsoft couldn’t be more extreme. Its Recall product, which took a screen recording every five seconds and stored its findings in clear text on the device, got a backlash from journalists and privacy campaigners. Microsoft has all but canceled the product, and its PR tail is between its legs. Apple’s ‘Crush’ ad has almost been forgotten.
Microsoft could make a mistake here. It is already working on products competing with OpenAI and might be tempted to go alone. What Bing is to Google, Microsoft AI will be to OpenAI. If it does so, it will once again shoot itself in the foot. OpenAI is far ahead in features and capabilities. Google cannot integrate it. Microsoft has gained an advantage from having done so. Apple too. Don’t bite the hand that feeds you seems an apt reminder.
This week’s essays focus a lot on the social impact of innovation and venture capital.
Ted Gioia’s essay about “Universe 25” focuses on the Durkheim concept of ‘anomie.’ It is the idea that our isolation leads to meaninglessness in life.
“More than 100 years ago, sociologist Emile Durkheim studied the problem of anomie. That’s not a word you hear very often nowadays. But we need to bring it back.
Anomie is a sense that life has no purpose or meaning. The people who suffer from it are listless, disconnected, and prone to mental illnesses of various sorts. Durkheim believed, for example, that suicide was frequently caused by anomie.
But the most shocking part of Durkheim’s analysis was his view that anomie increased when social norms were lessened. You might think that people rejoice when rules and regulations get eliminated. But Durkheim believed the exact opposite.”
Gioia examines the aimlessness of a world where people live in social media.
The Venture Capital essays are excellent. Sam Altman’s ‘Startup Playbook’ contains intelligent advice for startup founding teams. And Mario Gabriele’s piece about ‘How to Find a Unicorn’ has good advice for emerging fund managers. Omri Drory’s piece: How VCs Become A******s - is both funny and true. A great read
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