Is It The Best AI So Far?

Is It The Best AI So Far?

Artificial intelligence is developing rapidly. The minute we get used to one success, another comes along to change our expectations. The new model, the Claude Opus 4.7, introduced by Anthropic recently, is one such change. The rollout often goes beyond just AI chatbots and makes AI a trusted, independent digital partner. Even for developers and … Read more

Qwen Team Open-Sources Qwen3.6-35B-A3B: A Perception-Language Model for Sparse MoE with 3B Functional Parameters and Agentic Coding Capabilities

Qwen Team Open-Sources Qwen3.6-35B-A3B: A Perception-Language Model for Sparse MoE with 3B Functional Parameters and Agentic Coding Capabilities

The open source AI space has a new entry worth paying attention to. The Qwen team at Alibaba released the Qwen3.6-35B-A3B, the first open weight model from the Qwen3.6 generation, and it makes a strong argument that parameter efficiency is more important than raw model size. With 35 billion parameters but only 3 billion activated … Read more

OpenAI Launches GPT-Rosalind: Its First Life Science AI Model Designed to Accelerate Drug Discovery and Genomics Research

OpenAI Launches GPT-Rosalind: Its First Life Science AI Model Designed to Accelerate Drug Discovery and Genomics Research

Drug discovery is one of the most expensive and time-consuming endeavors in human history. It takes about 10 to 15 years from target discovery to regulatory approval of a new drug in the United States. Most of that time is spent not in moments of success, but in hard analytical work – sorting through mountains … Read more

Building a Transformer-Based NQS for Frustrated Spin Systems with NetKet

Building a Transformer-Based NQS for Frustrated Spin Systems with NetKet

The intersection of many body physics again deep learning open a new frontier: Neural Quantum States (NQS). While traditional methods struggle with complex systems with high dimensions, the global attention method of Transformers provides a powerful tool to capture complex quantum correlations. In this lesson, we use the research grade Variational Monte Carlo (VMC) pipe … Read more

UCSD and AI Research Together Introduce Parcae: A Stable Architecture for Large-Scale Language Models That Achieves the Quality of a Converter Twice the Size

UCSD and AI Research Together Introduce Parcae: A Stable Architecture for Large-Scale Language Models That Achieves the Quality of a Converter Twice the Size

The basic recipe for building better language models hasn’t changed much since the Chinchilla era: use more FLOPs, add more parameters, train on more tokens. But as deployment of inference consumes an ever-increasing share of computing power and deployment of models approaches the edge, researchers are increasingly asking a difficult question – can you scale … Read more

How to Build a Universal Long-Term Memory Framework for AI Agents Using Mem0 and OpenAI

How to Build a Universal Long-Term Memory Framework for AI Agents Using Mem0 and OpenAI

In this tutorial, we build a long-term memory layer for AI users to use Mem0OpenAI models, and ChromaDB. We are building a system that can extract structured memories from natural conversations, store them mathematically, retrieve them intelligently, and integrate them directly into the responses of a personal agent. We go beyond simple chat history and … Read more

Google AI Launches Gemini 3.1 Flash TTS: A New Benchmark for Predictable and Controllable AI Speech

Google AI Launches Gemini 3.1 Flash TTS: A New Benchmark for Predictable and Controllable AI Speech

Google has launched Gemini 3.1 Flash TTSA text-to-speech preview model that focuses on improving speech quality, expressive control, and multilingualism. Unlike previous iterations that prioritized easy conversion, this release emphasizes natural language audio tags, native support for more than 70 languages, and native multi-speaker chat. This release marks the transition from ‘black box’ audio generation … Read more

Google DeepMind Releases Gemini Robotics-ER 1.6: Brings Advanced Thinking and Machine Learning to Physical AI

Google DeepMind Releases Gemini Robotics-ER 1.6: Brings Advanced Thinking and Machine Learning to Physical AI

Google DeepMind’s research team has unveiled Gemini Robotics-ER 1.6, a significant development in its integrated thinking model designed to act as the ‘cognitive brain’ of robots operating in real-world environments. The model focuses on the critical thinking capabilities of robots, including visual and spatial perception, task planning, and success detection – serving as a high-level … Read more