AdapTive-LeArning Speculator System (ATLAS): Faster LLM inference

Together AI has introduced the AdapTive-LeArning Speculator System (ATLAS), a suite of inference innovations that optimize large language models for faster, cheaper, and more efficient performance. ATLAS is an adaptive-learning speculator system that dynamically improves at runtime, offering automatic performance improvements without manual tuning, and has achieved speeds of up to 500 TPS on certain models, outperforming standard decoding and specialized hardware.

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After the AI boom: what might we be left with?

The current AI investment boom is unlikely to leave behind a lasting, open infrastructure like the dotcom era's fibre networks, as most of the money is being spent on proprietary, short-lived systems and hardware. However, if the AI bubble bursts, the resulting surplus capacity could still drive innovation if the industry can find ways to open up its infrastructure, making it a shared public platform rather than a private surplus.

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Ridley Scott's Prometheus and Alien: Covenant – Contemporary Horror of AI (2020)

Here is a 2-sentence summary of the text: Science fiction movies have long addressed pressing social and philosophical issues, and the contemporary resurgence of the genre reflects a collective unease with the impact of technology, particularly artificial intelligence, on human identity and society. The Alien franchise, which began in 1979, is a prime example of this trend, with its exploration of themes such as feminism, capitalism, and the blurring of lines between human and machine, and its prequels, Prometheus and Alien: Covenant, specifically tackling the horror of AI and its potential to supplant humanity.

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Major security breach at Austrian AI startup localmind.ai

Es gab einen erneuten Versuch, sich rechtswidrig Zugang zu den Systemen von Localmind zu verschaffen, der jedoch dank neuer Sicherheitsmaßnahmen abgewehrt werden konnte. Localmind arbeitet weiterhin an der Verstärkung ihrer Sicherheitsmaßnahmen und hat bereits umfassende technische und organisatorische Maßnahmen umgesetzt, um die Sicherheit ihrer Systeme zu erhöhen.

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AI tools churn out 'workslop', but 'the buck' should stop with bosses

A recent study found that over 40% of US employees have received AI-generated content, known as "workslop," that lacks substance and is "destroying productivity." While AI technology and big tech companies may be partly to blame, the responsibility for effectively implementing and utilizing AI tools ultimately lies with employers, who must invest in training and planning to ensure their employees can use these tools effectively.

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Airbnb: Agent-in-the-Loop: Data Flywheel for LLM-Based Customer Support

The Agent-in-the-Loop (AITL) framework integrates human feedback into live customer operations to improve a large language model (LLM)-based customer support system, reducing retraining cycles from months to weeks. A production pilot demonstrated the framework's effectiveness, resulting in significant improvements in retrieval accuracy, generation quality, and agent adoption rates, highlighting the benefits of embedding human feedback loops into operational workflows.

ArXiv

Google researchers introduce "ReasoningBank" AI agent reinforcement learning

ReasoningBank is a novel memory framework that enables large language model agents to learn from their past experiences, both successes and failures, and integrate new learnings to become more capable over time. By combining ReasoningBank with memory-aware test-time scaling (MaTTS), agents can generate diverse experiences, synthesize higher-quality memories, and establish a powerful synergy between memory and scaling, leading to improved effectiveness and efficiency in various benchmarks.

ArXiv

Coral Protocol: Open infrastructure connecting the internet of agents

Coral Protocol is a decentralized infrastructure that enables communication, coordination, and trust among AI agents from different domains and vendors, allowing them to work together seamlessly. By establishing a common language and framework, Coral facilitates efficient and secure interactions among agents, unlocking new levels of automation, collective intelligence, and business value through open collaboration.

ArXiv

Let's take esoteric programming languages seriously

Esoteric programming languages, despite being challenging to learn, offer a unique set of features and constraints that can improve programming ability and provide a rich variety of artistic and computational exploration. This essay analyzes the appeal of esoteric languages, examining their benefits for program comprehension, language design, and pedagogy, and identifies reasons why they can be a valuable tool for programmers to improve their skills and awareness.

ArXiv

Agentic Context Engineering: Evolving Contexts for SelfImproving Language Models

The ACE framework is introduced as a solution to improve context adaptation in large language model applications, preventing issues such as brevity bias and context collapse by using structured, incremental updates to preserve detailed knowledge. ACE has been shown to outperform strong baselines in various benchmarks, achieving significant improvements in performance while reducing adaptation latency and rollout cost, and can even adapt effectively without labeled supervision.

ArXiv

Edge AI for Beginners

The EdgeAI for Beginners course is a comprehensive introduction to Edge Artificial Intelligence, covering topics from fundamental concepts to production-ready implementations, including small language models, hardware-aware optimization, and real-time inference. The course is divided into eight modules, with hands-on workshop materials and sample applications, aiming to empower learners to harness AI's potential on edge devices and address critical modern challenges such as privacy, security, and cost efficiency.

Repo

Show HN: Pyversity – Fast Result Diversification for Retrieval and RAG

Pyversity is a lightweight library that efficiently diversifies retrieval results by re-ranking items to encourage diversity and reduce redundancy, implementing strategies such as MMR, MSD, DPP, and Cover. The library is fast and scalable, with a simple API, and can be used in various domains, including e-commerce, news search, and academic retrieval, to improve exploration, user satisfaction, and coverage.

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Show HN: Databite – An open source integration library

The Databite SDK is a comprehensive TypeScript SDK for building, managing, and executing connectors to third-party APIs, providing a powerful and type-safe way to create integrations with external services. It is built as a modular monorepo with various packages, including a core SDK, flow engine, sync engine, and pre-built connectors, allowing developers to create robust data pipelines and manage data synchronization.

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Show HN: The Annotated Discrete Diffusion Models for Text Generation

This repository contains a Jupyter Notebook that implements a character-level discrete diffusion model for text generation, inspired by recent research on discrete score-matching and adapting Andrej Karpathy's baby GPT architecture. The model generates text by denoising all tokens in parallel, offering a powerful alternative to autoregressive models, and the notebook serves as both an educational guide and a research starting point for diffusion-based language modelling.

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ROSA+: RWKV's ROSA implementation with fallback statistical predictor

ROSA+ is an extension of the statistical next-token predictor ROSA, which provides a fallback Witten-Bell predictor for unknown sequences and allows for training and sampling on individual sequences. It can generate novel text sequences that do not appear in the training dataset, but lacks the deeper contextual understanding of neural network-based models, instead relying on a database-like understanding of text to stitch together sentences and demonstrate grammar.

Repo