- Famous for ChatGPT, one of the most popular AI chatbots
- Also created DALL·E (AI image generator) and GPT-4 (language model)
- Focused on developing advanced AI responsibly
- Based in the USA

- Google’s AI research team
- Known for AlphaGo, AlphaFold, and Gemini (formerly Bard)
- Pioneers in deep learning, AI research, and AGI development

Anthropic is an AI company focused on building safe, honest, and reliable AI.

Their most famous product is Claude, an advanced AI chatbot, similar to ChatGPT, but designed with extra focus on safety, transparency, and helpfulness.

Anthropic believes AI should be developed carefully to avoid risks, and many experts trust their approach.

Meta AI is the artificial intelligence research team behind Facebook, Instagram, and WhatsApp.

They’re working on:
✔️ LLMs (Large Language Models) — AI that can chat, translate, and assist
✔️ AI for the Metaverse — smarter virtual spaces
✔️ AI tools inside apps like Facebook and Instagram

Meta AI is one of the world’s biggest AI research labs, with huge investments in language, vision, and virtual reality.

Microsoft is a global tech leader investing heavily in AI.

They:
✔️ Partnered with OpenAI, helping bring ChatGPT to millions
✔️ Built Copilot — AI tools for Office apps (Word, Excel, etc.)
✔️ Added AI into Bing Search, making it smarter

Microsoft’s AI is now part of daily tools many people use — transforming search, productivity, and coding.

Tesla isn’t just electric cars — they’re pushing AI for the future of transport.

Tesla AI is building:
✔️ Autopilot & Full Self-Driving (FSD) — AI that can drive cars
✔️ Tesla Bot (Optimus) — A humanoid robot for everyday tasks

Tesla believes advanced AI is key to safer roads and making robots help with physical work.

Known as "China's Google," Baidu leads in search engines, autonomous vehicles, and AI research.

- Developed ERNIE Bot, China’s version of ChatGPT
- Focused on LLMs, AI translation, and smart mobility
- Pioneering self-driving cars and AI-powered maps

One of the world’s largest tech companies, Tencent uses AI across:

- Gaming — Smarter, adaptive in-game experiences
- Healthcare — AI for medical data and diagnostics
- Finance — AI for fraud detection and financial services

Social Media — AI for apps like WeChat

Tencent combines AI research with real-world products used daily by millions.

The tech giant behind China’s biggest e-commerce platforms, Alibaba uses AI to:

- Power product recommendations and search
- Optimize logistics and delivery
- Run AI cloud services for businesses

Develop LLMs for translation and communication

- SenseTime — One of the world’s largest AI vision companies:
- Specializes in facial recognition, smart cities, and surveillance
- Provides AI for security, retail, and public services

- AI for smartphones, cloud services, and smart devices
- Developing AI chips and infrastructure
- AI for 5G networks and enterprise solutions

Together, they drive China’s AI progress in vision, security, and next-gen hardware.

• Leading in multi-step reasoning and tool use benchmarks
• Excels at coherent conversation and API integrations
• 🔗 https://chat.openai.com/

• High scores on reasoning and “safety” metrics, excels at follow-up tasks
• Built-in “Extended Thinking” mode for complex workflows
• 🔗 https://www.claude.ai/

Gemini 2.5 Pro

• Top performer on the LMArena leaderboard, multimodal (text + vision)
• Great at cross-media queries and summarization
• 🔗 https://ai.google/

Grok 3 (xAI)

• Strong on factual accuracy tests, less restrictive prompting
• Integrates with Aurora image-gen for multimodal replies
• 🔗 https://grok.com

ERNIE X1 (Baidu)

• China’s top LLM, strong on Chinese-language benchmarks
• Competitor to Western models at lower compute cost
• 🔗 https://yiyan.baidu.com/

generating high-resolution, photorealistic images from text prompts

540 billion-parameter LLM that tops benchmarks like BIG-Bench and sets new standards in reasoning and code

structures for nearly every known protein, revolutionizing biology and drug discovery.

, an open-source text-to-image model that democratizes art generation on consumer GPUs.

Dec 2022 – 🐲 Baidu debuts ERNIE Bot (powered by ERNIE 3.0 Titan), China’s first major chatbot rival, trained on massive multilingual data.

featuring the new Transformer Engine and up to 80 GB of HBM3—fueling next-gen AI training and inference.

Feb 2023 – 💎 ChatGPT Plus launches as a paid fast-access tier, and Microsoft integrates ChatGPT-style AI directly into Bing search.

🤖 OpenAI releases GPT-4, a multimodal model (text + images) that scores in the top 10% on professional exams, powering the new ChatGPT.

🤖 Anthropic debuts Claude, its first large-scale conversational AI rival to ChatGPT.

🎨 Midjourney V5 goes live (Mar 16), delivering leap-frog improvements in image quality, realism, and prompt nuance.

Jul 2023 – 🦙 Meta/Microsoft open-source LLaMA 2 (7 B–70 B parameters) for research and commercial use—democratizing access to large LLMs.

Aug 2023 – 🚀 Hugging Face raises $235 M (Series D at $4.5 B valuation) to expand its model hub, Transformers library, and “Infinity” inference service.

🖥️ Microsoft rebrands its AI stack as “Copilot”, embedding assistants into Windows 11, Edge/Bing, and Office apps.

📸 ChatGPT adds vision & voice, so Plus/Enterprise users can converse via images and speech.

🎨 OpenAI unveils DALL·E 3, integrated with ChatGPT for richer, more detailed text-to-image creation.

🇫🇷 Mistral AI open-sources Mistral 7B (7.3 B parameters) under Apache 2.0

🤖 Moonshot AI launches Kimi, a 100 B-parameter Chinese LLM with ≈200 K-character context (≈8× GPT-4’s).

🏛️ U.S. issues landmark AI Executive Order, mandating safety testing, watermarking, and fraud-prevention standards for advanced models.

Turbo, boosting multimodal capabilities and slashing inference costs as Ernie Bot hits 300 M users.

(faster/cheaper, larger context) and introduces Custom GPTs, letting anyone build domain-specific chatbots.

an open-source 34 B-parameter Chinese/English model that outperforms LLaMA 2 on key benchmarks.

🌟 Google unveils Gemini 1.0
(Ultra/Pro/Nano variants), its next-gen multimodal AI family.

🤖 Mistral ships Mixtral 8×7B, a 46 B “mixture-of-experts” model combining multiple lightweight experts for extra power.
Let me know when you’re ready for 2024, or if you’d like any edits here

(alpha) launches, introducing overhauled prompting, much-improved coherence, fine-grained control over small details (hands, text), new upscalers, and a more literal “raw” style option. (reddit.com)

“Gemini” and releases the Gemini Android app, bringing its chatbot to mobile and Search.

(Haiku, Sonnet, Opus), raising the bar on safety and reasoning for large conversational models.

(8 B & 70 B), powering new AI writing assistants in Facebook and WhatsApp.

predicting 3D structures and interactions of proteins, RNA, and DNA at unprecedented scale—transforming molecular biology.

Act, the world’s first comprehensive, risk-based AI regulation (transparency requirements, banned high-risk uses, mandatory safety testing).

(Series D at $2.8 B valuation) to scale its ultra-fast AI inference chips for data
centers.

, offering a 1 M-token context window for advanced document understanding.

a speed-optimized update to Claude 3 with faster inference and improved efficiency.

reissues ERNIE 4.0 Turbo, cutting inference costs by ~90% and announcing 300 M Ernie Bot users

2 (123 B parameters, 128 K-token context) under Apache 2.0—one of the largest permissively-licensed LLMs to date.

launches (7 B parameters specialized for STEM), delivering strong math and logic reasoning for researchers and students.

alongside V6.1, unifying Discord and browser workflows and adding in-browser editing and upscaling. (en.wikipedia.org)

reaches 200 M weekly active users, solidifying AI chat as a mainstream tool.

$1.5 B from Saudi Arabia at LEAP to build an AI data center in Dammam powered by its inference hardware.

, allowing opt-in storage of user preferences and personal details for more natural, personalized output

(1.5 B & 9 B), an open-source coding LLM supporting 52 languages and a 128 K-token context window.

an efficiency-optimized open LLM with top-tier benchmarks at low inference cost.

the fastest member of the Claude family, excelling in high-throughput settings.

its text-to-video model generating 20 s high-def clips (plus a “Turbo” tier for faster output) within ChatGPT.

(developer preview) with native image/audio generation and early agentic tool-use capabilities.

Groq announces a landmark deal at LEAP 2025 to build a Groq-powered AI data center in Dammam. Their deterministic inference chips promise 2× lower latency than GPUs, targeting hyperscale LLM deployments.

• Size & Context: ~200 B parameters, 128 K-token window (4× GPT-4’s)

• Capabilities: Dramatically improved long-form reasoning—summarizes entire books in one go—and native code execution sandbox for safe plugin trials.

• Benchmarks: +15 pts on MMLU vs. GPT-4, near-human scores on law/professional exams.

A new research paper introducing an evolutionary-search layer for LLM fine-tuning. By simulating “mutations” in model weights and selecting top performers, AlphaEvolve achieves 20 % faster convergence on reasoning tasks while requiring 30 % less compute.

(developer preview)
• Deep Think Mode: Adaptive multi-step reasoning pipelines that decompose complex queries into tool-calls + internal chains.
• Multimodal Upgrade: First model to natively process 4K-resolution images and 60 s audio clips in a single pass.
• API Beta: Available to 500+ enterprise partners for feedback ahead of public launch.

In their Discord Office Hours, Midjourney teases V7’s “Neural Style Transfer 3.0,” promising photo-realism indistinguishable from professional photography, plus “Conceptual Blending” for merging vastly different motifs.

• Architecture: 600 B parameters with a dual-stream vision-language core.
• Performance: Outperforms GPT-4o on Chinese reasoning benchmarks by 10 %; 50 % faster inference via sparsely activated experts.

at Baidu Create 2025
• ERNIE 4.5 Turbo: 180 B-param multimodal LLM with 256 K-token context.
• X1 Turbo: Lightweight 50 B model optimized for real-time voice assistants in UX devices.
• Ecosystem: Rolled into Baidu Maps, Apollo Auto, and iQiyi video recommendations.

Sonnet-4 (fast, 75 B), Opus-4 (balanced, 200 B)
• New Feats: Real-time code execution with rollback safety; mixed-modal “WhisperSpeak” audio dialogue; 64 K-token memory that persists across sessions.
• Safety: New guided-alignment layer reduces hallucinations by 35 % in internal stress tests.

: “Deep Think” for complex reasoning; “Flash” for sub-50 ms replies on common queries.
• Agentic Tools: First wide release of autonomous agents that can browse, book appointments, and handle multi-step transactions.
• SDK: Now supports JavaScript, Python, and a low-code “PromptFlow” drag-drop interface.

• Magistral Small (24 B, Apache 2.0): Reasoning-focused, excels on logic/math benchmarks (GSM8K, MATH)
• Magistral Medium (proprietary 60 B): Enterprise-grade with built-in retrieval augmentation and vector DB plugins.