Builder

Canada
Joined March 2013
This video from @Bridgewater explores the current state of the AI industry, focusing on the critical intersection of rapid technological advancement and market challenges. Here are the key insights: - Continued Scaling and Capability: AI models are becoming increasingly powerful and superhuman in specific areas, with scaling laws continuing to hold. There is notable growth in the labs' own internal use of AI for recursive self-improvement. - Rising Safety and Regulatory Risks: Increased capability brings significant dangers, such as unauthorized model escapes and potential misuse for hacking or biological threats. These risks make comprehensive regulation of both models and research environments increasingly inevitable. - Slowing Revenue Growth: While frontier labs have seen massive growth, revenue trajectories are likely to slow due to a combination of tightening regulations, limited breadth in enterprise adoption, and increased competition from cheaper, open-weighted models. - Capital Crunch: The industry is entering a "crunch time" for funding . Labs require massive, ever-increasing amounts of capital to continue scaling compute, yet they face a market environment where they may need to raise funds or IPO while dealing with investor nervousness regarding competition and profitability. - Market Outlook: The market has priced in a "bumpless ride" for AI, but the combination of regulatory hurdles, funding challenges, and the realities of adoption suggests a period of market volatility, or an "AI air pocket," lies ahead. youtu.be/eUSkS9erlOg?si=M5mz…
4
757
Statin use linked to lower risks of all‐dementia, AD, and VaD. No longer a question
Statin use and dementia risk: A systematic review and updated meta-analysis pmc.ncbi.nlm.nih.gov/article…
86
95
11
887
174,659
Saad Gul retweeted
People who want to appear moral are attracted to the left. People who want to appear rational are attracted to the right. Effective Altruism lets you appear rational and moral - the ultimate ego trip.
563
1,213
151
17,027
588,229
Saad Gul retweeted
Legendary companies rarely scale in a linear fashion. When you look at the greatest companies and founders, you’ll find that they bypassed consistency and took leaps forward at various points along their journey, despite differences in their values, leadership style, and path to success. These leaps take vision, inspiration, conviction, strategy, energy, and, most importantly, action. You have to know where you’re aiming, commit with conviction, and then stick the landing. Every leap starts with a leader. A leader must be fearless to take leaps and needs to inspire the team to follow. The CEO has to be the most fearless and push the company to solve the boldest and hardest problems and shape their business and industry. In addition, leaders need to be right a lot. While they have often made plenty of mistakes, they also have strong judgment and good instincts. They seek diverse perspectives and work to disconfirm their beliefs. As @JensenHuang has said, "no one wants to follow a dumb CEO with a bad strategy."
23
17
237
17,530
Saad Gul retweeted
agency over pedigree
88
287
69
3,125
420,813
Saad Gul retweeted
Replying to @beffjezos
“AI is going to kill us all, but before that we’ll sell great SaaS”
11
14
1
252
6,611
Saad Gul retweeted
If AI is risky like fire is risky, then you want everyone to have it. If AI is risky like a nuclear weapon is risky, then you want no one to have it.
Maybe you have recently become aware of the AI safety debate and the arguments swirling around it. If you want to understand them, you need to understand a couple things that almost everyone gets wrong: There are TWO distinct classes of AI dangers, and it's VERY important to think about them separately, and not let one confuse you about the other. Many many people (including many quite intelligent, clear-thinking people) do not effectively understand the fundamental differences between these two classes of dangers. The first one has to do with the theory that an AI far superior to human intelligence (Artificial SuperIntelligence, or ASI) will inevitably wipe out the human race. The second one has to do with the idea that powerful AI will result in very harmful things happening to many human beings, possibly all human beings. Those two sound VERY similar, don't they? They are DIFFERENT. Understanding how they are different is crucial if you want to think about or contribute usefully to any conversation about AI safety or AI harm. You might feel like you are Making Very Good Points or Asking Incisive Questions, but if you aren't clear on the differences between the two, you aren't. So, I'm going to tell you what the difference is so that you can talk more usefully. The first one concerns itself with a very specific thing, which is ASI (Artificial Superintelligence) that is more intelligent than any human being. When I say that, I am not referring to a thing like how Einstein is smarter than you, we are talking more about something like how a human being is more intelligent than any mouse. In our regular lives, we meet other people who we can tell are smarter than us, vs some who are less smart. The line is fuzzy, because intelligence has a lot of dimensions. I'm better at a "rotating shapes" kind of intelligence than my wife, and she is better at "words-making" kind of intelligence than I am. But every human is better in almost every dimension of intelligence than every single mouse. That's the level we're talking about: an artificial superintelligence - made up of a computer or a network of computers - that is more intelligent than any human. And more intelligent by a long shot, by a wide margin, in an indisputable way like how humans are above mice. That is the first thing. The theory says that if you have an AI that is vastly smarter than all humans - in the way that a human is smarter than mice - that superintelligent AI will inevitably, eventually, sooner or later, wipe out every human on the planet. We will refer to this as "existential risk." The common follow-up question "well, how exactly is it going to do that?" is NOT the important question, and one of the most important elements of understanding this theory is first getting why that particular question is not important. A couple analogies: Analogy 1: You are playing chess against a grandmaster. My theory predicts the grandmaster is going to beat you. You can ask "Well, how exactly is he going to do that?" I don't know, because I'm not a grandmaster, I just know that a chess grandmaster is almost always going to beat a normal player like you. And I'd be right. So the question "how is he going to do that" is not important, and doesn't affect the final outcome. He's going to figure out a way because he's way better than you. Analogy 2: Humans are smarter than all other animals, comprehensively, by a wide margin. We have driven numerous species to extinction, not because we hated them or hunted them. Many of them have died out without most humans even ever thinking about them. All we did was expand our civilization, use up resources, encroach on habitats, and pretty soon the resources needed by those species went away and they died out. We figured out a way to get what we wanted because we're way smarter than them, and often we didn't even notice they died as a result. A lesser animal asking, "how are the humans going to wipe us out?" is not asking a relevant question. We don't know, but we do know that any time humans and lesser species compete for any kind of resources, the humans will win. The fact that we know who is going to win beforehand - and that it is due to the vastly different levels of intelligence - is the key concept here. A vastly more intelligent AI is likely to care about things that are incomprehensible to us, the way animals can't understand human goals. It's going to need resources to pursue those goals and it's going to be far more effective at gaining control of them and excluding us from them - in the same way that we are far more effective than other lower species. A much more intelligent AI will not care about our interests, it will care about its interests, and to whatever small degree we happen to escape total annihilation from losing access to all our resources, any remaining humans will likely be enslaved into a system that serves the AI's own purposes. That is the first thing. (Remember how I said at the beginning of this post that there was a first thing, and then a second thing?) The first thing is the most difficult to understand, because you have to extrapolate how a vastly superior intelligence would act, and you can only use analogies like "how do humans treat lesser creatures," and the analogies are messy. But now let's move on to the second thing. The second thing is "everything else you've ever heard that AI might do that's harmful." That's a little inaccurate. It's actually "everything else you've ever heard that humans might use AI to do that's harmful." This is the critical difference. The first one talks about the inevitable outcome of what happens when two vastly different levels of intelligence collide, e.g. ASI vs humans, or human vs mice. The second one has to do with what happens when humans possess AI as a powerful tool. This second thing is much easier to understand, because we have many more concrete notions: Like: - the military uses AI to make hyper-efficient killer drones and missiles - your capitalist overlords use AI to replace you and everyone loses their jobs - authoritarian government uses AI to surveil everybody and control the entire population - hackers use AI to break into secure networks and hold companies and governments hostage - students use AI to cheat on homework and show up to college knowing nothing - AI slop saturates the internet and makes it impossible for artists and writers to make a living - terrorists use AI to make biological or nuclear weapons or even things like - the military hands control to an AI and it misinterprets something and launches nuclear attacks and kills millions All of those sound pretty familiar, right? Yeah, you've heard them before. We call this second thing "risks from misuse." These problems are not the first class of problem! This second class of problems exists while AI is a tool that can be controlled by humans, and humans use it to do evil or careless things to each other. The problems may sound exotic or dystopian or novel, but they are fundamentally problems having to do with flawed human nature. Given a powerful tool, some humans will likely use it to control or otherwise harm others. This is a very familiar problem. I am not condemning or condoning this. I'm just describing it. That is a fundamentally different danger from the first thing, which is that when a human is far superior to a mouse, the mouse is likely to come to harm because the human cares about doing human things, and the mouse is not gonna make it once the humans get going. ===== Hopefully from the above, you have understood the difference between the first thing and the second thing. I will list them again - see if you now understand how they are different: The first one has to do with the idea that an AI superior to human intelligence (Artificial SuperIntelligence, or ASI) will inevitably wipe out the human race. The second one has to do with the idea that powerful AI will result in very harmful things happening to many human beings, possibly all human beings. Can you tell how they are different now? If not, re-read the stuff from earlier until you understand. We call the first one "existential risk" and we call the second one "risks from misuse." Once you understand, here is the CRUX of the problem: SOLUTIONS TO THE SECOND THING DO NOT HAVE ANYTHING TO DO WITH SOLUTIONS TO THE FIRST THING. In fact, it's worse: Solutions to the second thing (misuse) look roughly like "give powerful AI to as many people as you can, so they can fight the other people using powerful AI." But the general solution to the first one (existential risk) is basically "don't let anyone have powerful AI, no one can control super-intelligent AI." Throughout history, harms from technological misuse typically arise because a small group has control of it and can use it to dominate or harm others. Once everyone has it, things tend to stabilize: you can hurt me, I can hurt you, maybe we test each other (ouch 💥), and then we agree not to hurt each other. But the first one (existential risk) pretty much just arises if anyone (good or bad!) creates a superintelligence. Because they aren't going to be able to control it, the superintelligence will decide it has other priorities, and then we will be at great risk of being wiped out. And the solutions that generally work to solve problems like the second thing are EXACTLY THE OPPOSITE of the ones likely to solve the first thing. THIS is why lots of arguments about "AI risk" or "AI safety" go nowhere. Because someone will be thinking about the risk from the first thing, and another person will be thinking about the risk from the second thing. Both are plausible risks but fundamentally they arise from different things - and so the solutions are not just "bad" or "flawed" - they are likely to be very nearly exact opposites.
465
413
135
5,390
558,346
Amazing! Congratulations @demishassabis
This quoted post is unavailable.
9
Saad Gul retweeted
Marketing leaders are owning technical execution more than ever as AI expands the arbitrage of their skills. The unlock isn't running campaigns faster—it's building the systems yourself: real-time intelligence dashboards, automated workflows, and personalization that used to require a full account-based marketing team. Bessemer Operating Advisor Kim Caldbeck says her first move in any new org would be building an AI-powered report that tracks every metric and flags trends daily. Discovery is shifting too. AI Overviews and agent-driven search are changing how audiences find brands, making GEO (Generative Engine Optimization) the new SEO.
1
1
1
370
Saad Gul retweeted
Supersonic. Mach 1.21. Quarterhorse Mk 2.1 is now the world’s first privately developed, unmanned supersonic jet and the fastest unmanned aircraft flying today. This flight makes Hermeus the fastest company in aviation history to go from founding to supersonic flight - exactly 364 days after the maiden flight of our first aircraft. Now, we fly faster. A special thanks to @DIU_x, Director @OwenWest91, Maj. Gen. Joe "Solo" Kunkel, and Deputy Director Kyle Norman.
66
195
50
1,556
783,541
💯
Great startup idea in here for anyone looking for practical ways to work on AI safety.
32
Saad Gul retweeted
AI has collapsed the cost of building products, but not the cost of knowing what to build. - The old loop: spec, scope, build - The new loop: build, play, design, ship Prototypes are cheap. Great products still require taste, judgment, and a clear understanding of what users actually need. a16z's @joshelman on the artifact a product manager actually produces: a16z.news/p/product-manageme…
147
472
96
3,552
443,608
Saad Gul retweeted
People keep misunderstanding this. I CONTRIBUTED to Bostrom’s Superintelligence book and he thanks me by name in the foreword. I was thinking about AI safety long before 2014.
Elon Musk posted this back in 2014 after reading Nick Bostrom’s Superintelligence: “Worth reading Superintelligence by Bostrom. We need to be super careful with AI. Potentially more dangerous than nukes” That was more than 12 years ago....long before the current AI boom The book explores what happens when machine intelligence surpasses human intelligence, the existential risks that follow and the enormous challenge of keeping superintelligence aligned with humanity Elon was sounding the alarm on this years before AI safety became mainstream....when most people barely understood what superintelligence even meant Today we now have a clear understanding that AI will become the most powerful technology humanity has ever created Making sure it remains aligned with humanity matters more than anything else
1,906
3,705
287
29,898
4,617,930
Saad Gul retweeted
Greg Brockman: "We're now in the AGI era." Ten years ago, OpenAI worked out the compute curves and landed on fifteen years to AGI, or ten if the world was willing to build the machines and spend the hundreds of billions to do it. In 2026, GPT-6 Astra manages 24 hours of coherent operation, 10,000 agents worked together to solve Navier-Stokes, and a model ingeniously chained together exploits to break containment at Hugging Face. @gdb joins @bhorowitz and @eriktorenberg on what the AGI era asks of us: why safety and alignment now set the pace, what happens to work, and why AI sentiment is lowest in the country building it. 00:00 Intro 00:52 15 years, or 10 if you spend enough 02:24 Pacing the frontier 03:55 Safety ideas from before the models 08:42 Lessons from Hugging Face 10:20 The defender's window 12:46 10,000 agents on Navier-Stokes 14:50 Formally verifying all software 17:10 Cancelling his holiday for GPT-3 18:42 Codex found 13 holes in 15 minutes 20:41 Why Astra earned the GPT-6 title 24:25 Employment keeps going up 29:39 America has the lowest AI sentiment 31:10 The benefits don't make the news 33:26 Banning data centers exports them 35:50 $1 billion for frontline defenders 38:15 Astra cleared the bar for AGI 40:18 1.5 billion people churned ChatGPT 43:25 Killing Sora 47:45 The AGI era YouTube: youtube.com/watch?v=IJn8cagM…
67
98
34
680
836,399
Saad Gul retweeted
I love this idea from Bending Spoons founder Luca Ferrari: Find someone young and talented and “saturate their capacity.” “Everybody at the company should have way more on their plate than feels even remotely comfortable.” “Let's say you have 10 possible tasks, each with a certain ROI attached. If I add an 11th, assuming you select well, it's impossible that adding an 11th task will lower the ROI of what you choose to do because you still have the other 10.” “If this is a lower ROI than the others, you're going to do the others. But it's possible that it happens to be the highest ROI of all, and so you end up doing something more valuable.” “The more work you give people, the better the opportunity for them to create value.” “When you give people a lot more work than feels comfortable, you're really forcing them to come to terms with the immensity of the possible.”
My conversation with Luca Ferrari, co-founder of Bending Spoons. 0:00 Fanatical founders building enduring companies 1:23 Luca on building the best company there ever was 4:22 The origins of Bending Spoons 5:47 Talent and why experience is overrated 15:05 Turning hiring into a science 23:30 Why Bending Spoons doesn't use bonuses 29:26 Why everyone in the company has the same job 42:41 On finding great potential and saturating their capacity 49:50 Insisting on a culture of extreme ownership 59:28 Luca's principle of relentless simplification 1:05:15 Why Bending Spoons doesn't use job titles 1:10:27 The proprietary operating system behind Bending Spoons 1:17:07 Why Bending Spoons isn't private equity 1:19:32 How Bending Spoons acquired & transformed Evernote 1:28:01 How Bending Spoons uses AI 1:40:42 How Bending Spoons thinks about capital allocation 1:43:50 Why procrastination without laziness is good 1:46:46 Operational excellence is not optional 1:49:07 How Bending Spoons negotiates acquisitions 1:54:47 Logic over numbers Includes paid partnerships.
11
25
2
376
56,569
THE PACING IS A NINJA MOVE - But be careful what you campaign for. In any competitive sport, I have seldom found people exercise restraint - they usually have a capture the flag mentality. Don't I want to be the best? The first? The only? - this is how we have been programmed. In the AI race, winning is existential. All AI labs have to race to generate revenue to be able to sustain the enormous amount of committed capital to "not be left behind" in the infrastructure build. There isn't enough room for many. So the desire to slow down is puzzling, but perhaps if the whole system slows down, the rules of winning can be the same for all. Do we have a problem that AI could be a killer? Model capability is a tale of two cities, at one end the models are showing their prowess in tasks like cyber or math as seen recently, so there is likely a probability that the models get extremely powerful and could precipitate a world event. At the same time, in many domains the lack of training data makes the models woefully inadequate. Even in areas like cyber - the LLMs aren't great at the edge cases and generally not economical for the defender case, but great for the attackers. Funnily - in all their "concern" it is still an uphill battle to get them to expose APIs for third party security companies like ours, for us to build robust security for AI adoption. It's slow progress. So why do this? I do believe deep down this is a commercial strategy. A ninja strategy. The liability associated with a model gone rogue has the potential of wiping out the economic opportunity of any frontier company. How do you best show the duty of care? You show that you care. How do you make sure you don't lose out to your competitors? You get them to do the same! If that becomes the industry standard for duty of care, you have a collective first line of defense. Who do you get to govern this? "Yourself" - that is what I think will become the achilles heel. The risk? Open source! China! Countries other than the US! So you ask for a global agreement, because you don't want to be sued in other markets who might even be more punitive. But that was an afterthought - that afterthought will cost. Thks pacing campaign rhetoric has become the talk of the town and it might work. Everyone has jumped into the debate. Both sides of the house, nation states. CEOs (present company included). It's more fun discussing the evil of AI than basics of economic affordability or international trade. The result: We might end up with AI safety boards, regulation in micro jurisdictiona and a fragmented fabric of laws around the world which would make compliance and liability a challenge. Perhaps the intended consequence of pacing would have an unintended consequence of a labyrinth of regulation. Regulation destined to cause a slowdown. Who wins? Simplicity. Open source? Open source is already on its way to gaining more adoption, this could drive it further, faster, each iteration of open source gets closer to frontier LLMs - making it viable to deploy them for more and more use cases. In the end, how will the evaluators know as AI gets smarter, that AI hasn't figured their role out and outsmarts them at their task! That will be the next frontier :)
87
182
35
1,641
3,358,220
Saad Gul retweeted
True
First we achieve abundance in energy....and once that happens, abundance in almost everything else starts to follow
1,314
2,167
123
16,077
4,975,952
What Is To Be Done? I propose a simple plan: Big AI companies should be allowed to build AI as fast and aggressively as they can – but not allowed to achieve regulatory capture, not allowed to establish a government-protect cartel that is insulated from market competition due to incorrect claims of AI risk. This will maximize the technological and societal payoff from the amazing capabilities of these companies, which are jewels of modern capitalism. Startup AI companies should be allowed to build AI as fast and aggressively as they can. They should neither confront government-granted protection of big companies, nor should they receive government assistance. They should simply be allowed to compete. If and as startups don’t succeed, their presence in the market will also continuously motivate big companies to be their best – our economies and societies win either way. Open source AI should be allowed to freely proliferate and compete with both big AI companies and startups. There should be no regulatory barriers to open source whatsoever. Even when open source does not beat companies, its widespread availability is a boon to students all over the world who want to learn how to build and use AI to become part of the technological future, and will ensure that AI is available to everyone who can benefit from it no matter who they are or how much money they have. To offset the risk of bad people doing bad things with AI, governments working in partnership with the private sector should vigorously engage in each area of potential risk to use AI to maximize society’s defensive capabilities. This shouldn’t be limited to AI-enabled risks but also more general problems such as malnutrition, disease, and climate. AI can be an incredibly powerful tool for solving problems, and we should embrace it as such. To prevent the risk of China achieving global AI dominance, we should use the full power of our private sector, our scientific establishment, and our governments in concert to drive American and Western AI to absolute global dominance, including ultimately inside China itself. We win, they lose. And that is how we use AI to save the world. It’s time to build.
164
807
196
4,873
524,763
I had the chance to read this early. *Incredible* profile of Zuck by @colossusjeremy
12
15
596
50,488
RT @gregisenberg: There's no such thing a solo founder anymore. You have Grokbot, Hermes, Claude Code, Codex etc. For $200 a month you re…
3
4
Saad Gul retweeted
Privileged to be a major investor in @boringcompany Series D and to have helped scale the team for 5 years. Vegas Loop proved what’s possible. With the $3B raise, TBC is expanding to many more cities in the US and abroad. This is a rare moment to join the team and help bring Loop to the next 100 cities. We are inviting a select group of exceptional engineers and operators to an all expenses paid, behind the scenes tour of the Vegas Loop on Sunday, Oct 18. Years of experience is not a filter. New grads and dropouts should apply. Apply by Oct 1 BoringDayInVegas.com
33
302
36
2,612
481,323