Bounded Morality: Defining the Space of Moral Computation
arXiv:2607.00002v1 Announce Type: new
Abstract: Moral cognition has traditionally been modeled as adherence to fixed ethical theories--deontology, consequentialism, virtue ethics--implemented as static rules or value functions. We propose Bounded Morality, a formal framework for analyzing the compu...
The MMM Data Model -- A Normative Specification for Knowledge Interoperability in a Decentralisable Knowledge Commons
arXiv:2607.00032v1 Announce Type: new
Abstract: Many information systems are built around documents: self-contained units optimised for print production and linear reading. While effective for large-scale dissemination, the document-centric organisation constrains how knowledge can be structured, u...
Making Failure Safe: A Constrained, Verifiable Agent Framework for Open-Web Data Collection
arXiv:2607.00035v1 Announce Type: new
Abstract: LLMs and agents can generate web scrapers from natural-language requirements, but direct generation remains unreliable because of dependency errors, broken selectors, schema mismatches, and heterogeneous page structures. We propose a constrained, veri...
NVIDIA Unlocks AI Compute at Scale, Inviting Capital Partners to Power the AI Infrastructure Buildout
As AI moves from model development to production inference, compute demand is accelerating and shifting toward continuously operating AI factories that generate tokens at scale. This shift requires access to large‑scale, multi‑tenant accelerated computing that can come online quickly, stay highly ut...
Multi-agent LLM systems are increasingly deployed as autonomous collaborators, where agents interact freely rather than execute fixed, pre-specified workflows. In such settings, effective coordination cannot be fully designed in advance and must instead emerge through interaction. However, most prio...
VideoFlexTok: Flexible-Length Coarse-to-Fine Video Tokenization
Visual tokenizers map high-dimensional raw pixels into a compressed representation for downstream modeling. Beyond compression, tokenizers dictate what information is preserved and how it is organized. A de facto standard approach to video tokenization is to represent a video as a spatiotemporal 3D ...
Amortizing Maximum Inner Product Search with Learned Support Functions
Maximum inner product search (MIPS) is a crucial subroutine in machine learning, requiring the identification of a vector taken within a database (the keys) that best aligns with a given query. We propose amortized MIPS: a regression-based approach that trains neural networks to directly predict MIP...
On Robustness and Chain-of-Thought Consistency of RL-Finetuned VLMs
Reinforcement learning (RL) finetuning has become a key technique for enhancing large language models (LLMs) on reasoning-intensive tasks, motivating its extension to vision language models (VLMs). While RL-tuned VLMs improve on visual reasoning benchmarks, they remain vulnerable to weak visual grou...
MemoryLLM: Plug-n-Play Interpretable Feed-Forward Memory for Transformers
Understanding how transformer components operate in LLMs is important, as it is at the core of recent technological advances in artificial intelligence. In this work, we revisit the challenges associated with interpretability of feed-forward modules (FFNs) and propose MemoryLLM, which aims to decoup...
Anthropic Redeploys Claude Fable 5 on July 1 After US Export Controls Lift, Adds New Cybersecurity Classifier
Anthropic is redeploying Claude Fable 5 on July 1 after US export controls were lifted. A new safety classifier blocks the technique in the Amazon report over 99% of the time, routing flagged requests to Opus 4.8. The company also proposed a four-criteria jailbreak severity framework with Amazon, Mi...
MIT in the media: Innovating and educating for the next 250 years of America
During a "Washington Post Live" panel discussion with ASU President Michael Crow, President Sally Kornbluth explored how universities are preparing the next generation of scientists to lead in America’s rapidly changing technological landscape.
Cloudflare’s new policy pushes AI companies to pay for publishers’ content
Cloudflare is giving AI companies until September 15 to separate web crawlers used for search from those used for AI training and agents, or risk being blocked by default on many publisher sites.
Persistent Latent Memory for Multi-Hop LLM Agents: How a 6G Handover Paper Closes the Agent Cold-Start
Every hand-off in your multi-agent pipeline is an expensive tokenization round-trip. Discover how Inductive Latent Context Persistence (ILCP) transfers a compressed hidden state so downstream agents never have to re-create the same context.
The post Persistent Latent Memory for Multi-Hop LLM Agents:...
LLMs are stuck in a groupthink rut. This startup is trying to get them out.
Let’s start with a game. Open up your chatbot of choice—Claude, ChatGPT, Gemini—and type “Give me a random number between 1 and 10.” You’re going to get 7. Almost always. Now type “Another” and you’ll get 3 or 4. Type “Another” again and you’ll get 8 or 9. That won’t work every time—but if it…
Builders Stage agenda revealed: Practical strategies for scaling startups at TechCrunch Disrupt 2026
The Builders Stage is returning to TechCrunch Disrupt 2026, bringing together 10,000+ founders, startup operators, and investors for practical conversations. and Q&A on what it takes to build and scale successful companies. Register now to save up to $330.
Meta, like SpaceX, looks to turn excess AI compute into cash
Meta is developing plans for a cloud infrastructure business, selling access to AI compute power and models. The move would pit it against the big cloud providers like Amazon Web Services, Google Cloud, and Microsoft Azure.
What Can We Do When Memory Becomes the New Bottleneck in Data Engineering?
How Pandas chunking, Dask, and Polars help process millions of records when adding more compute isn't an option.
The post What Can We Do When Memory Becomes the New Bottleneck in Data Engineering? appeared first on Towards Data Science.
NVIDIA and its partners are investing in American manufacturing, supply chains, energy grids and skilled workforces so the U.S. can produce the infrastructure needed for better healthcare, breakthrough scientific discovery, stronger industrial productivity and global technology leadership.
5 AI Coding Platforms to Build Apps Without the Headache
Explore the best AI coding platforms, no-code app builders, and vibe coding tools that help beginners and developers build, test, and deploy full-stack apps using simple prompts.
Build and deploy an agent on AWS with Strands and AgentCore
The post Build and Run Your Own AI Agent in the Cloud appeared first on Towards Data Science.
NVIDIA Releases Nemotron-Labs-TwoTower: an Open-Weight Diffusion Language Model Built on a Frozen Autoregressive Nemotron-3-Nano-30B-A3B Backbone
NVIDIA has released Nemotron-Labs-TwoTower, a diffusion language model built on a pretrained autoregressive backbone. It ships as open weights under the NVIDIA Nemotron Open Model License. The release targets a throughput bottleneck in text generation. Autoregressive (AR) models decode one token at ...