Today marks a significant milestone in artificial intelligence with the launch of OpenAI's **o1 model**, a groundbreaking addition to the AI landscape. This model, codenamed "Strawberry," is designed to enhance reasoning capabilities by mimicking human-like thought processes, particularly in complex tasks such as coding, mathematics, and scientific problem-solving. **Key Features of the o1 Model:** - **Deep Reasoning:** The o1 model is engineered to spend more time "thinking" before responding, allowing it to tackle intricate problems more effectively than its predecessors. This includes a remarkable ability to solve multi-step challenges, achieving an impressive **83% accuracy** in a qualifying exam for the International Mathematics Olympiad, compared to just **13%** for its predecessor, GPT-4o. - **Two Variants:** OpenAI has introduced two versions: - **o1-preview**: Tailored for advanced reasoning tasks, particularly in STEM fields. - **o1-mini**: A more compact and cost-effective version, optimized for coding and math, priced significantly lower than o1-preview. - **Performance Benchmarks:** In competitive programming scenarios like Codeforces, the o1 model ranked in the **89th percentile**, showcasing its prowess in coding challenges. - **Innovative Training Method:** Unlike previous models that learned from patterns in data, the o1 model utilizes **reinforcement learning**, allowing it to learn from trial and error, which enhances its problem-solving capabilities. **Access and Availability:** Starting today, users of **ChatGPT Plus and Team** can access both o1-preview and o1-mini. Enterprise and educational users will gain access next week. OpenAI plans to extend o1-mini access to all free ChatGPT users in the near future. **Limitations to Note:** While the o1 model represents a leap forward, it currently lacks some features found in earlier models, such as web browsing and file uploads. Its processing speed may also be slower, reflecting its focus on deep reasoning.

Skild AI, a startup based in Pittsburgh, Pennsylvania, has recently made waves in the field of robotics and artificial intelligence (AI) - securing a $300 million funding. Founded by ex-Carnegie Mellon professors Abhinav Gupta and Deepak Pathak, Skild AI develops software to power various robots, including those with two or four legs. Their mission centers around creating a versatile AI brain for robots, aiming to achieve artificial general intelligence (AGI) in the physical world. What do you think could be the potential applications emerging from this technology?

In part 2 of 4 on AGI Guaranteed Dissent takes a look at 6 fundamental design differences in creating AI and biological intelligence. They are - design direction (outside-in vs inside-out) - organisational paradigm (deterministic substrate vs self-organisation) - boundary condition (decoupled vs continuous feedback) - learning method (defined training runs vs continuous development) - optimisation algorithm (prediction vs coherence) - energy consumption (GWh vs kWh) Please take a look and let me know what you think. https://open.substack.com/pub/bockster/p/thinking-fast-and-artificial?r=ionsk&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true

The evolving role of AI in the job market, emphasizing new career opportunities and the strategic approach needed to leverage generative AI effectively. Source: Standford online webinar. Highlights 🚀 AI models are improving rapidly; starting now is beneficial. 👩‍💻 Traditional roles will still exist, but new roles will emerge. 🌱 AI product managers are becoming essential in the workforce. 🔍 AI ethics specialists will play a crucial role in development. 🔗 Integration experts are needed to merge AI with existing systems. 📊 Understanding generative AI aids career advancement for non-tech professionals. 🎯 Prioritizing user-facing AI features is essential over chatbots. 📈 Focus should be on content consumption rather than just creation. 🛠️ Generative AI can enhance existing products significantly. 🧠 A strategic approach is vital for success in various industries. 📅 Companies must adapt to the changing landscape of AI job roles. 🌍 The democratization of AI will broaden job opportunities. 🤝 Bridging technical expertise with business strategy is key. 🚧 Challenges exist, but opportunities outweigh them in generative AI. 💡 Continuous learning and adaptation are crucial for future career growth. Check out my article on linkedin: https://www.linkedin.com/pulse/identifying-ai-opportunities-strategies-market-success-altaf-rehmani-lmlfc/ Source: https://youtu.be/XNqpySV97IU?si=AyEZb-7dUO2Q4pjt

📊 Key Insights from Deloitte's State of Generative AI in Enterprise Q3 Report Deloitte's latest report on Generative AI in the enterprise reveals critical trends and actionable insights: 🚀 67% of organizations are increasing GenAI investments due to strong early value 💡 Top benefits: Improved productivity (34%), innovation (12%), revenue increase (10%) 🎯 Key to driving value: Deeply embedding GenAI into business functions and processes Challenges & Actions: Data: 75% increased investments in data lifecycle management Risk & Governance: Only 23% feel highly prepared Scaling: Majority have deployed less than 1/3 of GenAI experiments to production Next Steps for Organizations: Build toward transformation beyond cost reduction Prioritize data quality and management Focus on fundamentals and adaptability Measure performance rigorously Implement responsible governance with clear accountability Are you seeing similar trends in your organization's GenAI journey? Let's discuss! Source: https://www2.deloitte.com/us/en/pages/deloitte-analytics/articles/advancing-human-ai-collaboration.html #GenerativeAI #EnterpriseAI #AIStrategy #DeloitteInsights