AI News - So 2027 AI Is Going To Be HUGE, Sam Altman reveals Key Milestones In AI, Googles New Model
AI Summary
- AI Expansion
- Rapid growth in AI, particularly in model releases.
- CEOs of top AI labs predict future developments.
- Metabot
- GitHub coding agent with 38% score on software engineering benchmark.
- Surpassed Devon, Alibaba Factory, and IBM Research.
- Utilizes a structured workflow: context gathering, planning, editing, testing, and submission.
- Open source and demonstrates rapid AI development.
- Google’s Gemma 2
- Two models released: one with 27 billion parameters, another with 9 billion.
- Outperforms llama 3, Coen, and command R in chatbot evaluations.
- Shows Google’s progress and potential leadership in AI.
- Google’s Gemini 1.5 Pro
- Features a 2 million token context window.
- Context caching introduced to reduce costs for developers.
- Indicates a trend towards longer context lengths in AI models.
- AI Model Costs
- Future AI models predicted to cost up to $100 billion to train.
- Expected to outperform humans in most tasks by 2027.
- Nvidia’s potential benefit from increased AI model training.
- AI in Science and Discovery
- AI could accelerate scientific breakthroughs and cure diseases.
- Specialized models may emerge for scientific research.
- AlphaFold’s success in protein folding suggests potential for AI in discovery.
- Humanoid Robots
- Liu Robotics launched humanoid robot KFU with Huawei’s multimodal LLM Pangu.
- China’s focus on humanoid robotics could lead to advancements.
- OpenAI’s GPT-4 Critic
- A model based on GPT-4 to critique and improve chatbot responses.
- Helps human trainers spot mistakes during reinforcement learning.
- Indicates a move towards AI models evaluating and improving themselves.