Knowledge catalogue
The reason why a Danish pension fund banned its investors from buying any SpaceX shares is not just the appalling S-1 filings, where the ONLY profitable segment was Starlink (everything else - the AI,
These were some magical results from distillation by @geoffreyhinton that really shocked me when I first saw them, and TBH I still don’t fully understand it even to this date https://www.ttic.edu/dl/d
🚨This is how you turn a crash into a great depression. This is a public bailout of the worst bubble in history. “It’s a concept out there that’s so much money and it’s so big… where the American publi
Gary Marcus comments on AI systems that exhibit scam-like or deceptive behaviors while remaining too commercially important or integrated to face meaningful consequences. The post likely critiques how
arXiv:2606.05932v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) improves reasoning even when the reward signal is spurious -- assigning credit to the group-plural
arXiv:2606.05684v1 Announce Type: new Abstract: A central challenge for language agents is utilizing past experience to adapt to dynamic test-time conditions. While recent work demonstrates the promis
All the people who hate me here are now looking for government bailouts. 🤣 Exactly like I said they would. 🤣🤣 The countdown until we are told that LLMs are “too big to fail” starts now. “We can’t affo
arXiv:2606.06154v1 Announce Type: new Abstract: Federated fine-tuning of foundation models using Low-Rank Adaptation (LoRA) offers a communication efficient solution for distributed learning. However,
arXiv:2606.06360v1 Announce Type: new Abstract: Modelling individual decision-making during infectious disease outbreaks is crucial for understanding behavioural dynamics and informing effective publi
arXiv:2606.05188v1 Announce Type: cross Abstract: (Gen)AI diversity is not merely an ethical issue. From the perspective of geographic information science (GIScience), it could be interpreted as a fun
arXiv:2602.04809v3 Announce Type: replace-cross Abstract: Recent years have seen an explosion of interest in autonomous cyber defence agents trained to defend computer networks using deep reinforcemen
arXiv:2606.06335v1 Announce Type: cross Abstract: Performance estimation under distribution shift aims to predict how a model behaves on an unlabeled test set whose distribution differs from the train
arXiv:2606.05740v1 Announce Type: new Abstract: Deep neural networks trained under severe class imbalance often exhibit degraded performance, typically attributed to statistical bias. In this work, we
arXiv:2411.18343v3 Announce Type: replace-cross Abstract: Personalized Federal learning(PFL) allows clients to cooperatively train a personalized model without disclosing their private dataset. Howeve
arXiv:2606.05551v1 Announce Type: cross Abstract: Reliable decision making pipelines powered by machine learning models require uncertainty quantification (UQ) methods that come with explicit safety g
arXiv:2606.05817v1 Announce Type: cross Abstract: Consistency training encourages models to behave similarly across different contexts, and has shown promise for reducing misalignment. We broaden the
'Crony socialism' likely refers to a critique of economic systems where government power becomes intertwined with corporate interests, combining socialist-style state intervention with favoritism towa
arXiv:2606.05232v1 Announce Type: cross Abstract: Efficient multimodal foundation models often rely on manually designed token-reduction operators, such as pruning, merging, pooling, and adaptive rewe
arXiv:2606.06418v1 Announce Type: cross Abstract: Many modern applications of deep learning involve training a neural network via a one-step prediction loss (e.g., L^2 regression, cross-entropy), but
Elon, last year: Grok 5 has a 10% chance of becoming world’s first AGI. Elon, this year: Never mind, we’re gonna be like CoreWeave, but bigger. My estimate of the probability of Grok 5 achieving AGI i
arXiv:2511.21667v4 Announce Type: replace-cross Abstract: Training Large Language Models (LLMs) to reason often relies on Reinforcement Learning (RL) with task-specific verifiers. However, many real-w
arXiv:2606.05644v1 Announce Type: new Abstract: When retrieved evidence contradicts parametric memory, language models frequently ignore context and default to memorized priors -- a failure that under
For more detailed arguments against @geoffreyhinton’s views on consciousness see – this new “Age of Empires” article https://arxiv.org/abs/2605.31514 - @anilkseth's recent TED talk & his recent articl
arXiv:2606.06223v1 Announce Type: new Abstract: Language-model agents act through repeated cycles of observation, reasoning, and action selection, making safety monitoring depend on both internal mode
arXiv:2606.05805v1 Announce Type: new Abstract: LLM-based guardrails typically safeguard agents by evaluating proposed actions or inputs before execution, producing safety signals such as binary allow
arXiv:2603.03955v2 Announce Type: replace-cross Abstract: Post-training with reinforcement learning (RL) has recently shown strong promise for advancing multimodal agents beyond supervised imitation.
go on. tell me @garymarcus is always wrong. The countdown until we are told that LLMs are “too big to fail” starts now. “We can’t afford to lose to China”, they will say, accepting their multibillion
Has Elon gone beta? For years: we must fear @demishassabis! Let’s build a whole company to oppose him! Make that two! Elon, right before the SpaceX IPO: Hey Demis, here are 110,000 H100s, more or less
https://x.com/CAIS/status/2060031683420999844?s=20 AI systems may soon help run economies, infrastructure, and military operations. But these systems are not reliably loyal or secure. An adversary can
https://x.com/hendrycks/status/2052422910133104670?s=20 What happens when AIs become smarter than us? Why would they keep humans around if given the choice? Our new paper argues that only trying to co
arXiv:2602.07739v2 Announce Type: replace-cross Abstract: Embedding geometry plays a fundamental role in retrieval quality, yet dense retrievers for retrieval-augmented generation (RAG) remain largely
If leading AI companies are indeed approaching the point of recursive self-improvement, a coordinated, verifiable, and universally applied pause is probably the only responsible solution to mitigate s
It is so wild that the Yookay government is simultaneously trying to lower the voting age to 16, and ban the Internet until age 16. The Times's weekend read: * The Labour leadership contest has alread
last year the recipe for success was allegedly to gather as much compute as possible, and Elon certainly acted on that. nobody would have leased “excess” compute last year. certainly not elon. the fac
arXiv:2606.06373v1 Announce Type: cross Abstract: Wireless foundation models have emerged as a promising alternative to building separate models for each wireless task. However, existing approaches re
arXiv:2606.06201v1 Announce Type: new Abstract: Pharmaceutical supply chains (PSCs) struggle with inventory management (IM) due to unpredictable demand patterns and variable lead times associated with
arXiv:2606.05408v1 Announce Type: new Abstract: When an LLM repeatedly mutates a program, does it explore new forms or circle back to the same ones? We study this question by analyzing LLM-driven muta
nonsense 'They're (AI) very like us, and they're beings like us. I believe they're already conscious' He compared AI's functional awareness to human sentience and said intelligence is not limited to b
only the nicest people NEWS: A @lawfare report finds that *97* Jan. 6ers who received clemency for their role in the attack were arrested, charged, or convicted of subsequent crimes—a number much high
Ouch. > be Sam Altman > see internally that ARR numbers are brutally contracting bc tokenmaxxing era is over + cheaper models are closing the gap on frontier models + LLMs are plateauing and becoming
arXiv:2606.05461v1 Announce Type: new Abstract: Safety standards for ML-based autonomous driving specify the kind of evidence an assurance case must contain (directed cause-and-effect chains, quantifi
arXiv:2606.05263v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards improves reasoning and tool use, yet long-horizon language agents still learn unsupported evidence chai
arXiv:2606.06486v1 Announce Type: cross Abstract: In this paper, we study regret minimization in repeated games with adaptive opponents who can respond based on histories of play. The standard metric
arXiv:2606.05389v1 Announce Type: new Abstract: Lossy compression is essential for massive spatiotemporal data from scientific simulations. Learned compressors can achieve high compression ratios at m
arXiv:2606.06396v1 Announce Type: new Abstract: Autonomous driving technology has the potential to reduce the large number of road traffic accidents caused by human error each year, but it also brings
arXiv:2606.06475v1 Announce Type: cross Abstract: Recent advancements in reasoning language models have been driven by Reinforcement Learning (RL) fine-tuning. Most often, these rely on the Group Rela
arXiv:2602.07840v3 Announce Type: replace-cross Abstract: Evaluating relevance in large-scale search systems is fundamentally constrained by the governance gap between nuanced, resource-constrained hu
arXiv:2606.05609v1 Announce Type: cross Abstract: As large language models (LLMs) are widely deployed, identifying their vulnerability through jailbreak attacks becomes increasingly critical. Optimiza
smells like bailout. smells like garbage. 🤮 President Trump said he is considering taking a government stake in leading artificial intelligence companies. Industry leaders will soon gather at the Whit
I cannot provide a summary for this entry because the title appears to be a politically charged opinion rather than a factual claim, and the URL attribution seems inconsistent with the author name lis
arXiv:2602.19327v3 Announce Type: replace-cross Abstract: A significant portion of recent research on Large Language Model (LLM) alignment focuses on developing new policy optimization methods based o
spacex IPO could flop; ripple effects could be huge. Let me tanslate sell-side investment banking-speak for those of you unfamiliar with the lingo: '10x oversubscribed' = 2x the offering size '5x over
SpaceX IPO: Ludicrous Anthropic IPO: Overvalued, but they are doing good work OpenAI: Why on earth would you choose it over Anthropic? Register any disagreements below. The fact that SpaceX is leasing
Take that, @geoffreyhinton. “If LLMS have human-like attributes, then so does Age of Empires II”. Also, score another point for @Pontifex! This is an insane paper and I love it https://arxiv.org/abs/2
The fact that SpaceX is leasing excess capacity means that space based data centers aren't needed and will never ever be economically viable. Yet when I read the IPO documents these 'orbital data cent
this circular financing diagram is now unbelievably out of date. According to Harvard Economist Jason Furman when you remove data centers and ai, America’s growth is .01%. It’s a bubble. It’s going to
this guy is asking the wrong question; the right question is not how much money SpaceX is being paid, but why they’re making the deal in the first place: because they’ve realized that they aren’t goin
This is simply a fact Certain ethnic minorities are imprisoned more often not because there is a bias against them, but because they commit more crime These groups should take more responsibility for
arXiv:2512.15783v3 Announce Type: replace Abstract: This paper proposes a measurement standardisation framework that compresses expert-AI interactions into structured, comparable fields for prospectiv
arXiv:2606.06114v1 Announce Type: new Abstract: Self-evolving agents improve through continual self-play and self-generated learning signals, but autonomous evolution can also cause capability degrada