The Archive

RRM augments multimodal memory graphs with reflection mechanisms for long-horizon video reasoning agent adaptation.

OPLD uses on-policy latent distillation to train flexible latent visual reasoning without external trace supervision.

Ablation study on deep learning architectures for automated TCM tongue diagnosis achieves F1 0.66 on 5k-image dataset.

ParliamentBench evaluates deceptive reasoning in 16 LLMs via Secret Hitler game framework with 1,600 adversarial matches.

Philosophical critique argues LLM anthropomorphisms (hallucination, agency, sentience) reflect category mistakes in asymmetric human-machine language games.

LM-GRASP reformulates combinatorial optimization as online imitation learning, training Transformer constructive policies from scratch per problem instance.

Pre-registered audit compares LLM tutoring pedagogical vs. direct-answer policies; Claude Opus 4.8 and GPT-5.6 Sol judge helpfulness signals.

FinSMART applies market-aligned reinforcement learning to financial sentiment analysis for algorithmic trading.

ConMem framework estimates diagnostic value of inspection logs for LLM-assisted steel-equipment screening and early-risk detection.

Label-free criterion selects optimal unsupervised domain adaptation algorithm and hyperparameters for medical imaging without target-domain labels.

Information bottleneck framework ensures faithful time-series forecast explanations via interpretable-by-design approach with faithfulness guarantees.

Comparative study finds LLMs and linguist trainees struggle similarly with subjective Appraisal theory annotation in TED talk discourse.

AI engineers adopt ontologies to constrain probabilistic agents within deterministic logical boundaries, reviving semantic web techniques.

It is impossible to make large language models fully secure against hacks because of a fundamental flaw in how they work, a team of researchers argue in a paper presented at the International Conference on Machine Learning, a top AI conference, this month. The claim has huge implications for the safety of this technology, which…

OpenAI reduces GPT-5.6 pricing for Luna and Terra variants, emphasizing efficiency gains for enterprise AI deployment.

Microsoft pitched its own homegrown AI models, harnesses, and even a Mythos competitor on Wednesday, telling Wall Street it plans for continued growth.

avatarin deployed GPT-Realtime for Yamada Denki retail support; 30K users in 2 weeks with 92% positive feedback.

Overview of AI applications in healthcare covering use cases, benefits, and implementation challenges.

Cohere overview of AI applications in manufacturing: use cases and implementation considerations for industrial operators.

Latent Space observes AI adoption accelerating in financial services as the next major vertical after software engineering.

Microsoft reports strong cloud revenue growth but modest M365 AI monetization despite high capex.

As Meta pours billions into AI infrastructure and agents, Zuckerberg is working to convince investors that the payoff will be worth the price.

When Microsoft reported killer fourth-quarter earnings for its fiscal 2026 year (which ended June 30), it tucked in an interesting little tidbit about how its investments in the two biggest, and competing, AI labs are doing.

On the company’s second-quarter earnings call Wednesday, CEO Mark Zuckerberg said Meta sees a “large enterprise opportunity” spanning AI agents, APIs, compute, and internal software.

Microsoft is working on an AI "super app" that combines Copilot's chat, coding, and agentic capabilities. During an earnings call on Wednesday, Microsoft CEO Satya Nadella said the app will span "both consumer and commercial experiences" when it launches this year. "Copilot is evolving rapidly from chat to Cowork to Autopilots," Nadella said. "This quarter, we are bringing these Copilot experiences together, including code, in one super app… This is a major step forward, and I look forward to sharing more soon." Nadella's confirmation comes months after a report from Fortune revealed that Mic...

Separating the chaff from the wheat in Anthropic results is hard. We take a stab anyway.

Meta is all-in on AI, and sometime soon, the company is going to make a big push into personal AI agents that can do things on your behalf. On Wednesday's Q2 2026 earnings call, CEO Mark Zuckerberg previewed a high-level vision of how the company is thinking about personal agents and what it will do to make them viable for users - and how it will convince less technical people to give them a shot: Soon we will have agents that can work 24/7 on your behalf to help you achieve your goals and improve your life, your health, your relationships, your finances, whatever you want. The first domain t...

At TechCrunch Disrupt 2026, the AI Stage is back to dig into the single hottest topic in the community for the past few years, presented by Google for Startups.

D. Richard Hipp (SQLite creator) draws historical parallel between SQL's labor displacement and current AI impact on programming roles.

Weng previously served as the VP of AI Safety Research at OpenAI.