Machine Learning Research - The Batch | DeepLearning.AI (Page 3)

A performance comparison table highlights Ling-1T's success in reasoning and coding tasks against rivals.

Machine Learning Research

Reasoning Without “Thinking”: All about Ant Group’s Ling-1T, an open, non-reasoning model that outperforms closed competitors

Reasoning models typically learn to undertake a separate process of “thinking” through their output of before they produce final response. Ant Group built a top non-reasoning model that can take similar steps as part of its immediate response.

Image shows MolmoAct system processing "Put the plate in the dishwasher" through spatial reasoning.

Machine Learning Research

Better Spatial Perception for Robots: MolmoAct creates spatial maps for robots to plot their actions before executing text directions

Robot control systems that accept only text input struggle to translate words into motions in space. Researchers developed a system that enables robots to plan spatial paths before they execute text instructions.

Close-up of a violin scroll and pegs, symbolizing precision needed in fine-tuning AI models.

Machine Learning Research

Fine-Tuning Simplified: Thinking Machines’ new Tinker API makes it easier to fine-tune models on many GPUs

The first offering from Thinking Machines Lab, the startup founded by former OpenAI CTO Mira Murati, aims to simplify — and democratize — the process of fine-tuning AI models.

Graphs compare DeepSeek models showing reduced cost per million tokens with V3.2-Exp over V3.1-Terminus.

Machine Learning Research

DeepSeek Cuts Inference Costs: DeepSeek-V3.2-Exp streamlines processing using a "lightning indexer," boosting efficiency

DeepSeek’s latest large language model can cut inference costs by more than half and processes long contexts dramatically faster relative to its predecessor.

Flowchart of Text-to-LoRA model processes task embeddings into LoRA adapters, showing weights and losses.

Machine Learning Research

LoRA Adapters On Tap: Text-to-LoRA generates task-specific LoRA adapters directly from natural language descriptions

The approach known as LoRA streamlines fine-tuning by training a small adapter that modifies a pretrained model’s weights at inference. Researchers built a model that generates such adapters directly.

Bar chart comparing performance of Qwen3 models against others in diverse tasks, highlighting Qwen3-Max.

Machine Learning Research

Qwen3 Goes Big (and Smaller): Alibaba expands Qwen3 family with a 1 trillion-parameter Max model, open-weights Qwen3-VL, and the Qwen3-Omni voice model

Alibaba rounded out the Qwen3 family with its biggest large language model to date as well as smaller models that process text, images, video, and/or audio.

Comparison table highlighting Claude Sonnet 4.5's top scores in coding and reasoning benchmarks, featuring improved capabilities.

Machine Learning Research

Claude Levels Up: Anthropic launches Claude Sonnet 4.5 and the Claude Agent SDK, and overhauls Claude Code for developers

Anthropic updated its mid-size Claude Sonnet model, making it the first member of the Claude family to reach version 4.5. It also enhanced the Claude Code agentic coding tool with long-desired features.

Image illustrates data flow from raw satellite sources through processing to embeddings for climate tracking.

Machine Learning Research

Earth Modeled in 10-Meter Squares: Google’s AlphaEarth Foundations tracks the whole planet’s climate, land use, potential for disasters, in detail and at scale

Researchers built a model that integrates satellite imagery and other sensor readings across the entire surface of the Earth to reveal patterns of climate, land use, and other features.

Electron microscope image of bacteriophages with distinct hexagonal heads and tails on a gray background.

Machine Learning Research

AI Generates Viral Genomes: Researchers use genomic language models to create custom viruses

Researchers used AI models to create novel viruses from scratch.

Flowchart shows data reordering, probability sampling, and effective gradient updating in reinforcement learning.

Machine Learning Research

Faster Reinforcement Learning: New technique auto-selects training examples to speed up fine-tuning

Fine-tuning large language models via reinforcement learning is computationally expensive, but researchers found a way to streamline the process.

Chart details ChatGPT conversations. Writing (28.1%), info-seeking (21.3%), and guidance (28.3%) lead.

Machine Learning Research

What ChatGPT Users Want: ChatGPT users now more likely to be young, female, and seeking info, study shows

What do ChatGPT’s 700 million weekly active users do with it? OpenAI teamed up with a Harvard economist to find out.

Central AI agent icon links to merchant, cart, and payment symbols, illustrating agentic payments process.

Business

Agents of Commerce: Google’s AP2 gives developers new tools to build agentic payments

Google launched an open protocol for agentic payments that enables agents based on any large language model to purchase items over the internet.