ChatGPT maker OpenAI Just Announced it Latest Model

OpenAI just shocked the AI world with ‘o1’, its new AI model which the company claims "thinks" before responding — and it outperforms humans on PhD-level science questions.

The new model, o1, marks a major step in AI scaling by increasing the compute time for inference, allowing the model to process questions more thoroughly before answering. This approach enhances reasoning capabilities, especially for logic-based tasks, by spending more time "thinking" according to the company.

While not universally superior to previous models like GPT-4o, o1 is designed for scenarios where deeper logical processing is valuable. OpenAI has also released o1-preview, a trial version, and o1-mini, a cost-effective model targeting STEM (Science, Technology, Engineering, and Mathematics) applications. These models outperform GPT-4 in science and math; for example, they scored 83% in the International Math Olympiad qualifier, while GPT-4 managed only 13%. Both are available now for ChatGPT Plus and Team users, with broader access planned soon.

Our Thoughts:

First of all, it's a bit worrying to see more and more anthropomorphism, but we can't underestimate the significance of this moment.

The idea of a model capable of doing more than just recognizing patterns, but actually thinking before providing answers is pretty cool.

If this model lives up to the hype, it has the potential to unlock breakthroughs in fields like medicine, engineering, and possibly other challenges we haven’t been able to solve.

The future is bright.!!!

Google’s robots master shoelace-tying

Google DeepMind has just unveiled two new AI systems that advance robot dexterity. Now, machines can perform complex tasks that require dextrous movement, such as tying shoelaces and hanging shirts.

The details:

• The first system, ALOHA Unleashed, enables robots to perform five complex tasks using both arms, such as tying shoelaces, hanging shirts, and repairing other robots.
• The second system, DemoStart, utilizes reinforcement learning to teach robots intricate behaviours in a simulated environment, requiring 100 times fewer demonstrations than traditional methods.

These systems employ diffusion methods similar to image generation models to anticipate robot actions from random noise. In simulations, robots achieved a 98% success rate, and in real-world tasks such as cube reorientation, they achieved up to 97% success.

Why it matters:

Although robots still can't do things as well as humans, these improvements are a big step toward making robots that can do everyday tasks better. Using image techniques in robotics also shows that getting better in one part of AI can help other parts improve too.

QUICK HITS        

• Google began rolling out Gemini Live to free users on the Gemini Android app — offering natural voice conversations with the AI assistant and 10 new voice options.
• Salesforce unveiled Agentforce, a suite of low-code tools for building autonomous AI agents capable of reasoning and completing tasks in sales, service, marketing, and commerce.
• OpenAI's ChatGPT reportedly surpassed 11 million paying subscribers, including 1 million on higher-priced business plans, potentially generating over $2.7 billion in annual revenue, according to COO Brad Lightcap.
• Mastercard agreed to acquire AI-powered threat intelligence company Recorded Future for $2.65 billion, aiming to enhance its cybersecurity capabilities.
• Google introduced DataGemma, the first open models designed to connect large language models with real-world data from Google's Data Commons, aiming to reduce AI hallucinations by grounding responses in factual stats.
• Hume AI launched Empathic Voice Interface 2 (EVI 2), a new voice-to-voice foundation model trained for emotional intelligence, capable of understanding and generating various tones of voice and speaking styles.

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THAT’S A WRAP