MIT's new fine-tuning method lets LLMs learn new skills without losing old ones

MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, continuously learning agent.
CIO

Predicting the future is easy — deciding what to do is the hard part

AI agents help businesses stop guessing — linking predictions to actions so teams can move from “what might happen” to ...
InfoWorld

AI-augmented data quality engineering

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...
IEEE

Aligning Crowd-Sourced Human Feedback for Reinforcement Learning on Code Generation by Large Language Models

Abstract: This paper studies how AI-assisted programming and large language models (LLM) improve software developers' ability via AI tools (LLM agents) like Github Copilot and Amazon CodeWhisperer, ...
Hosted on MSN

Supervised learning example explained with real-life use case

What is supervised learning and how does it work? In this video/post, we break down supervised learning with a simple, real-world example to help you understand this key concept in machine learning.
Microsoft

Agent Lightning: Adding reinforcement learning to AI agents without code rewrites

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...
VentureBeat

Vibe coding platform Cursor releases first in-house LLM, Composer, promising 4X speed boost

The vibe coding tool Cursor, from startup Anysphere, has introduced Composer, its first in-house, proprietary coding large language model (LLM) as part of its Cursor 2.0 platform update. Composer is ...
IEEE

RLCoder: Reinforcement Learning for Repository-Level Code Completion

Abstract: Repository-level code completion aims to generate code for unfinished code snippets within the context of a specified repository. Existing approaches mainly rely on retrievalaugmented ...
marktechpost

Microsoft AI Introduces rStar2-Agent: A 14B Math Reasoning Model Trained with Agentic Reinforcement Learning to Achieve Frontier-Level Performance

Large language models have made impressive strides in mathematical reasoning by extending their Chain-of-Thought (CoT) processes—essentially “thinking longer” through more detailed reasoning steps.
Scientific Research Publishing

Ribba, B. (2023) Reinforcement Learning as an Innovative Model-Based Approach: Examples from Precision Dosing, Digital Health and Computational Psychiatry. Frontiers in ...

ABSTRACT: Depression treatment often involves a complex and lengthy trial-and-error process, where clinicians sequentially prescribe medications to identify the most ...
ZDNet

Claude can teach you how to code now, and more - how to try it

Anthropic launched learning modes in Claude chatbot and Claude Code. Instead of creating answers, they use the Socratic approach to guide you. You can select 'Learning' from the style dropdown to ...
Engadget

Anthropic brings Claude's learning mode to regular users and devs

This past spring, Anthropic introduced learning mode, a feature that changed Claude's interaction style. When enabled, the chatbot would, following a question, try to guide the user to their own ...