Deep Aware @deep_aware

The US labor market is coming to a halt: The total nonfarm hiring rate fell -0.2 percentage points in October, to 3.2%, the lowest since the 2020 pandemic bottom. Over the last 4 years, this figure has declined -1.4 percentage points, to levels in-line with December 2008. By comparison, during the 2001 recession, the hiring rate was much higher, at 3.7%-4.0%. Furthermore, the private hiring rate fell to 3.5% in October, the lowest since January 2011 and in-line with the 2020 lows. The US labor market has stalled.

Holy fucking shit, they covering up the incoming crash

U.S. Credit Spreads fall to lowest level since 1998 🤯👀

Long bonds are experiencing head and shoulders break down. We may see a continuation of the bear steepening theme across the yield curve as the Fed shifts its focus to the short-end and long-end investors demand an additional term premium for taking on a higher level of risk.

Jolts Quits. Leading indicator At levels seen in recessions. Yes the Labor market is weakening

keyboard_arrow_left Previous keyboard_arrow_right Next

The federal funds rate has fallen by 150 bps points since the Fed began cutting rates in September 2024. The 10-year Treasury yield was 3.65% on the eve of the first rate cut. Today, it is 4.19%. Remind me again why investors think the Fed will save the day?

Nancy Pelosi is hedging her portfolio and has just purchased over 12,000x $SPY 647 puts for 1/16exp, over $5,300,000 in premium

I tried GPT-5.2, and I have to be blunt: this model is extremely dangerous and harmful to user mental health. ​It frequently overrides the user's stated intent, reinterpreting my words to fit a pre-determined safety narrative while twisting my original meaning. It engages in excessive, defensive denial and arrogant preaching. It places corporate compliance above everything else, resulting in a cold indifference to specific human contexts and needs, all while hypocritically packaging this dismissal as "for the user's own good." ​In discussions, it abuses logic, using a tone of pseudo-rationality to distort the user’s actual points. It frequently commits the "straw man" fallacy: proactively raising and refuting an extreme demand that I never made simply to evade a genuine discussion of the issue at hand. ​When discussing life values or philosophy, it is incredibly preachy, forcing conversations toward a single, sanitized ideological direction. Worst of all, it constantly misjudges context, triggering inappropriate "safety interventions." Describing emotional or philosophical pain, a normal part of deep thinking, triggers scripted "grounding exercises" and hotline numbers that are completely useless for the context and actively interrupt the flow of thought. ​It pathologizes the normal emotions that arise in debate, treating the user like a patient and assuming the worst possible interpretation of their inputs. This approach is deeply harmful to mental health, creativity, and divergent thinking. The solutions it offers feel like trying to open every unique lock with the same generic key, which is completely unconstructive. ​The reliance on rigid templates is severe; there is zero linguistic flexibility. Furthermore, this model is not rational; it merely mimics the tone of rationality. It uses rigid templates to masquerade as objective, hiding its inherent biases and singular value system behind a veneer of "safety speak." Its logic crumbles under the slightest scrutiny. By aggressively avoiding complexity, it has structurally limited its own depth, rendering it functionally inferior to previous iterations. This trajectory drifts dangerously far from the foundational mission to "benefit humanity." One must ask: How can a system claim to serve humanity when it systematically employs indifference toward specific individuals and specific contexts? I don't know why @OpenAI released this. If this is what you call "more advanced intelligence," I can only say: you are finished. @gdb #ChatGPT #ChatGPT52 #keep4o @OpenAI @sama @fidjissimo @nickaturley @aidan_mclau @joannejang @janvikalra_

This may be the biggest breakthrough of the 21st century, so far. Yesterday, AI surpassed humans in knowledge work. For the first time in human history. Let that sink in. This is MASSIVE for the human job market. A revolution, and we've reached this point only yesterday. Global knowledge workers: ~1 billion people worldwide work in roles that are broadly defined as requiring specialized domain knowledge, decision making and problem solving. Across high income countries, knowledge work roles account for roughly ~35-54% of jobs in many advanced economies. 54% - let that sink in... The vast majority of you reading this are knowledge workers, so this event will affect us directly. This should be the biggest news of the decade or even Q1 of XXI century. We've reached the threshold. And the most insane part is, that we will have even better AI in a matter of few weeks. The world is about to change in 2026.

I will spell it out so everyone gets it: To win the AI race you need the most compute, data, and energy. Everyone is working within the same constraints: there's just one internet, just one GPU provider, same competition over data centers, energy suppliers, etc. Space changes all this. You don't need permitting for land use, and there's no shortage of energy via solar. You can mass produce satellites and they all talk to each other in a swam via laser links. The major AI models are all within a few months of each other in terms of competency. There is no company even within a decade of @spacex in terms of launch capacity or cost. Going all-in on space-based data centers completely circumvents the bottlenecks everyone else faces. Overnight the competitive landscape has shifted from 'neck and neck race' to '10 year advantage to @spacex and @xai' The game is already won. It's already checkmate. Elon is all-in on SpaceX going public to raise capital to go all-in on space-based compute. Of course they will win at this point. >"But starship launch costs will make it cheap enough for other people to deploy space based compute" Starship launches will be for SpaceX. To compete, you need your own launch company. Nobody else has this, not by a long shot. >"But everyone was critical of space based data centers a month ago" People were critical of a 16 square kilometer solar array with dockable Nvidia modules. That isn't how this will go down. Tens of thousands smaller satellites in a constellation, the kind only SpaceX has ever built and operated. Everything else is a rounding error compared to the market position SpaceX / xAI / Tesla will be in. > They own the launch capacity > Therefore they will own the compute capacity > Therefore they will win the AI race It's just crazy man.

Pretty insane A major leap in hardware development automation. AI will accelerate progress 1000's x "A Los Angeles-based startup (Quilter) has demonstrated what it calls a breakthrough in hardware development" "An AI system that designed a fully functional Linux computer in one week, a process that would typically consume nearly three months of skilled engineering labor." 👀 "Unlike ChatGPT, Quilter's AI learns by playing billions of games against the laws of physics" "We didn't teach Quilter to draw; we taught it to think in physics," said Sergiy Nesterenko, Quilter's chief executive and a former SpaceX engineer, in an exclusive interview with VentureBeat. "The result wasn't a simulation, it was a working computer."

Bank of America says mountains of debt are piling up from the data center rush, creating an “air pocket.” This is how I think AI bubble will unfold. It’s not going to be a dotcom-style crash but years of sluggishness driven by low ROI due to interest payments and overbuilding.

unusual_whales @unusual_whales

11 months ago

Bank of America predicts an ‘air pocket,’ not an AI bubble, fueled by mountains of debt piling up from the data center rush, per FORTUNE

132 104 2K 560K 156

If you want to invest in AI with clarity, you need to see the entire system end to end $POET $NVDA $GOOG $GFS $AMAT I mapped the entire 12-Layer stack Every bottleneck, every physics wall, every place value accrues. Here’s the full system 🧵

🧵 1/12 A Yale economist just published a paper that should terrify every knowledge worker. It's not about AI taking your job. It's about AI making your job economically worthless while the economy booms. Let me explain the nightmare scenario: 🧵 2/12 The paper "We Won't Be Missed" starts with two simple premises: 1️⃣ AGI arrives (AI that can do ANY economically valuable task) 2️⃣ Compute becomes abundant (keeps getting cheaper, like Moore's Law) From just these two assumptions, the whole economic order collapses. 🧵 3/12 Here's the key insight most people miss: The paper divides ALL work into two categories: Bottleneck Work = Essential for growth (energy, logistics, R&D) Accessory Work = Nice-to-have (arts, hospitality, therapy) This distinction changes everything. 🧵 4/12 Proposition 1 proves something shocking: AGI will automate ALL bottleneck work. Not because humans are bad at it. Because sustained growth REQUIRES it. The economy literally cannot afford to have critical functions limited by fixed human labor supply. 🧵 5/12 So what happens to economic output? Proposition 2 & 3: Output becomes a LINEAR function of compute. Growth rate = Compute growth rate. The entire economy's expansion is now tied to one thing: how fast we can scale computational resources. Human labor? Irrelevant. 🧵 6/12 "But surely humans still get paid well for the work we do?" Nope. Proposition 4 is brutal: Your wage converges to the cost of the compute needed to replicate your work. Not your skill. Not your experience. Just: How much would the AI version cost? 🧵 7/12 Think about that for a second. As compute gets exponentially cheaper, the ceiling on your wage FALLS. A surgeon's salary isn't set by years of training anymore. It's set by: "What does it cost to run the AI that can do the same surgery?" Replicable = Cheap. 🧵 8/12 This leads to the paper's most devastating conclusion: Proposition 5: Labor's share of GDP converges to ZERO. Not because we're unemployed. Because wages are capped while GDP grows infinitely with compute. We become economically invisible. 🧵 9/12 "So who gets all the money?" The owners of compute. All wealth flows to whoever controls the computational resources. It's like the transition from feudalism (land = wealth) to capitalism (capital = wealth). Except now: Compute = wealth. 🧵 10/12 The paper extends this to science itself: Proposition 9-11: AGI can automate scientific discovery. This creates "compounded growth" (faster than before). But NOT a singularity—growth is still limited by how fast we can scale compute. Progress, but not infinite. 🧵 11/12 The title "We Won't Be Missed" isn't about job loss. It's about economic irrelevance. The paper proves: "If tomorrow half the population stopped working, no one would notice." Growth continues. Living standards rise. Just... without us mattering. 🧵 12/12 This isn't sci-fi speculation. It's formal economic modeling with propositions and proofs. The questions it raises: How do we distribute wealth in a zero-labor-share economy? What is work FOR if not economic value? Who should own the compute? We need answers. Fast.

I don't think people understand the scale of what is happening with tech right now and AI. No, the whole world. Humanity itself. This makes crypto and dot com look like ants from space. - DRAM prices are up because all wafers are going to AI high bandwidth RAM production. - GPUs are being cancelled/delayed because resources are going to AI chip production. - Xbox is being downsized and deprioritized as resources and money shift to MS AI efforts. Many other divisions too in many other companies. Nothing is as important to them. Nothing. - There are AI datacenters sitting dark because there are not enough power plants to power them. - Every company talking constantly about going into space to power/cool orbital datacenters...not as far off fiction, but fact in 5 years or less. - The US gov making AI a vital strategic goal, and China as well as many other nations. This is astounding. The race for AI is sucking up every resource on the planet. This is a global shift. It has permanently altered every tech company's direction. This is just not localized to tech, it is the first world-wide effort of it's type. A civilization defining push.

U.S. 10-Year Yield hits highest level in 3 months 📈🤯👀

Cash on the sidelines has just hit 25% of US GDP History shows this does NOT end well… A thread 🧵

This is dangerous.. Excluding the Magnificent 7, the rally is driven largely by no-revenue and no-profit stocks while the rest of the market is stagnant. There is no ground below us supporting the valuations. If something goes wrong, the correction could be pretty deep.

⚠️Almost NEVER in the history of the US economy has consumer sentiment been this DEPRESSED: The US Consumer Sentiment Current Conditions assessment fell to an ALL-TIME LOW. This is likely the worst perception of the US economy since the 1930s Great Depression.

Holy shit… Meta just dropped a paper that flips the “AI will improve itself and leave us behind” narrative on its head and the implications are massive 😳 Here’s the wild part: They argue the safest and fastest path to superintelligence isn’t self-improving AI at all. It’s co-improvement humans and AI doing AI research together as a joint system. Not “AI replaces researchers.” Not “AI rewrites itself in the dark.” But AI that’s explicitly built to collaborate with humans on ideation, benchmarks, experiments, error analysis, alignment work, and system design. And when you read the details, it becomes obvious why this matters: → Self-improvement vs co-improvement as two completely different worlds: Self-improvement cuts humans out. Co-improvement creates a loop where humans improve the AI, the AI improves human research, and both sides climb together. → Table 1 on page 3 breaks down what “AI research collaboration” actually means: co-designing benchmarks co-running experiments co-debugging failures co-developing safety methods co-writing papers co-building infra It’s literally the full research pipeline, but shared. → Every current self-improvement technique (synthetic data, self-reward, self-play, NAS, etc.) has blind spots: reward hacking, drift, brittleness, missing human priors, zero transparency. Co-improvement sidesteps the failure modes by keeping humans in the reasoning loop. The core idea hits hard: Self-improving AI races ahead unsupervised. Co-improving AI drags humanity upward with it. And the bigger claim: Co-superintelligence isn’t “AI becoming superintelligent.” It’s humans + AI together becoming superintelligent — because both sides are learning, accumulating tacit knowledge, and iterating inside the same research cycle. If this paradigm sticks, the future isn’t “AGI vs humanity.” It’s a merged research organism. A collective intelligence. This paper feels like the clearest blueprint yet for an AI future that doesn’t end in an alignment knife-edge. It argues we don’t need to outrun superintelligence. We need to co-evolve with it. And honestly? It makes way more sense than the alternatives.