Tagged articles

AI evolution

7 articles · Page 1 of 1

Machine Learning Algorithms & Natural Language Processing

Sep 14, 2026 · Artificial Intelligence

Astar: Alibaba & Zhejiang Univ's AI That Guides AI Evolution, Beating Human Experts 100x Faster

Alibaba and Zhejiang University's Astar learns from AI systems' own Git history to propose evolution strategies, achieving 54–68% single-shot success rates versus 31% for GPT-5.5 and 32% for human experts, and delivering 23.6% offline HitRate and 4.86% GMV gains in Lazada's ad system through 20 fully automated iterations.

AI evolutionAlibabaAstar

0 likes · 15 min read

Astar: Alibaba & Zhejiang Univ's AI That Guides AI Evolution, Beating Human Experts 100x Faster

SuanNi

Jun 14, 2026 · Artificial Intelligence

Where Can AI Evolution Go? DeepMind Maps the Path from AGI to ASI

DeepMind’s extensive report defines AGI as human‑level intelligence, outlines four plausible routes to superintelligence, examines the inherent advantages of digital cognition, and highlights the technical, economic, and societal frictions that could impede the transition from AGI to ASI.

AGIAI evolutionAIXI

0 likes · 10 min read

Where Can AI Evolution Go? DeepMind Maps the Path from AGI to ASI

21CTO

May 13, 2026 · Artificial Intelligence

Is AI Entering a Self‑Evolving Era? Baidu’s Robin Li Introduces the Daily Active Agents (DAA) Metric

Robin Li, CEO of Baidu, proposes Daily Active Agents (DAA) as the new AI‑era metric, arguing it better reflects platform value than Token or DAU by counting how many agents deliver results, and outlines a three‑layer evolution of agents, individuals, and organizations supported by a full‑stack AI infrastructure.

AI ecosystemAI evolutionAI infrastructure

0 likes · 10 min read

Is AI Entering a Self‑Evolving Era? Baidu’s Robin Li Introduces the Daily Active Agents (DAA) Metric

AI Cyberspace

Feb 15, 2026 · Artificial Intelligence

From GPT-1 to GPT-4o: A Deep Dive into the Evolution of Large Language Models

This article chronicles the rapid progression of GPT models from the 2018 GPT‑1 pre‑training breakthrough through GPT‑2’s multitask learning, GPT‑3’s scaling laws and few‑shot abilities, to GPT‑4’s multimodal capabilities and the 2024 GPT‑4 Turbo, Sora, and GPT‑4o releases, while also explaining core LLM abilities and the decoder‑only architecture of GPT‑2.

AI evolutionFew-Shot LearningGPT

0 likes · 20 min read

From GPT-1 to GPT-4o: A Deep Dive into the Evolution of Large Language Models

AI Architecture Hub

Dec 24, 2025 · Artificial Intelligence

From LLMs to Autonomous Agents: The Three Evolution Stages of AI

This article explains the three evolutionary stages of AI—from large language models that generate text, through workflow‑enhanced systems using retrieval‑augmented generation, to fully autonomous agents capable of self‑directed decision‑making—while detailing the four core technologies that power each stage.

AI evolutionAgentEmbedding

0 likes · 9 min read

From LLMs to Autonomous Agents: The Three Evolution Stages of AI

Programmer Xu Shu

Jun 23, 2025 · Artificial Intelligence

From Bag‑of‑Words to ChatGPT: How Large Language Models Evolved

Tracing the evolution of large language models—from early bag‑of‑words techniques, through word embeddings, RNNs, attention mechanisms, Transformers, BERT, and GPT—this article explains each breakthrough, its limitations, and how they culminated in ChatGPT’s conversational AI.

AI evolutionChatGPTLarge Language Models

0 likes · 12 min read

From Bag‑of‑Words to ChatGPT: How Large Language Models Evolved

21CTO

Feb 24, 2025 · Artificial Intelligence

From Transformers to DeepSeek-R1: Evolution of Large Language Models

Since the 2017 introduction of the Transformer architecture, this article chronicles the rapid development of large language models—including BERT, GPT series, multimodal systems, and the cost‑effective DeepSeek‑R1—highlighting key innovations, scaling trends, alignment techniques, and their transformative impact across AI research and industry.

AI evolutionDeepSeekLLM History

0 likes · 23 min read

From Transformers to DeepSeek-R1: Evolution of Large Language Models