AI is expected to create 97 million new jobs by 2025. At the same time, 85 million jobs may change or shift, resulting in a net gain of 12 million new opportunities. Here are some of the top AI breakthroughs that stood out to me: 𝟭. 𝗔𝗜 𝗶𝗻 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 AI is helping robots learn to perform complex tasks, like tying surgical knots or assembling tiny electronic parts. Techniques like imitation learning, where robots observe and mimic human actions, and reinforcement learning, where they improve through trial and error, make this possible. These advancements mean robots are becoming more adaptable and precise, opening the door to handling more challenging jobs in industries like healthcare, manufacturing, and beyond. 𝟮. 𝗔𝗜 𝗶𝗻 𝗖𝗮𝗻𝗰𝗲𝗿 𝗗𝗶𝗮𝗴𝗻𝗼𝘀𝗶𝘀 Harvard researchers have developed an AI tool called "Chief" that can identify rare cancers with incredible accuracy, even for metastatic cancers, achieving a 98% success rate. This tool doesn’t just diagnose; it also helps predict the most effective treatments. With AI like Chief, healthcare could become faster, more accurate, and accessible worldwide, making it easier to detect and treat illnesses early. 𝟯. 𝗚𝗼𝗼𝗴𝗹𝗲 𝗗𝗲𝗲𝗽𝗠𝗶𝗻𝗱’𝘀 𝗚𝗲𝗻𝗖𝗮𝘀𝘁 Google DeepMind’s AI tool, GenCast, can predict extreme weather events like hurricanes and floods with high accuracy. For example, it accurately tracked the path of Hurricane Alina, allowing emergency teams to prepare in advance. This technology has the potential to save lives, protect crops, and minimize damage caused by natural disasters.

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Add OpenAI o1 like reaasoning to any model. Hermes 3 70B with Forge is comparable to Gpt-4, Geminie Pro 1.5, and Claude 3.5 Sonnet on several benchmarks. Here is the blog post by Nous Research: https://nousresearch.com/introducing-the-forge-reasoning-api-beta-and-nous-chat-an-evolution-in-llm-inference/

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Devin is an automated junior engineer that has been designed to build, test, and ship code, reportedly outperforming 74.2% of human programmers. It is available for a subscription fee of $500 per month, which translates to about $8 per hour. This pricing model positions Devin as a cost-effective alternative to traditional software engineers, who can cost up to 100 times more. 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝗮𝗻𝗱 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹𝗶𝘁𝘆 𝟭. 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗠𝗲𝘁𝗵𝗼𝗱: Devin operates exclusively through Slack, allowing users to tag it for tasks that would typically require a developer's intervention. This design choice aims to cater to non-programmers and enterprise workers who frequently use Slack. 𝟮. 𝗪𝗼𝗿𝗸𝘀𝗽𝗮𝗰𝗲 𝗖𝗿𝗲𝗮𝘁𝗶𝗼𝗻: When a task is requested, Devin spins up a workspace that includes a shell, browser, and editor, enabling it to write, run, and test code, ultimately sending pull requests to GitHub. 𝟯. 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗘𝗻𝘁𝗿𝗶𝗲𝘀: Devin creates knowledge entries to provide context for the tasks it handles, which helps in maintaining continuity and understanding of the project. 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗮𝗻𝗱 𝗟𝗶𝗺𝗶𝘁𝗮𝘁𝗶𝗼𝗻𝘀 • 𝗖𝗼𝗱𝗲 𝗤𝘂𝗮𝗹𝗶𝘁𝘆: Devin has shown the ability to write decent code, but it exhibits typical AI quirks, such as including unnecessary packages and occasionally hallucinating explanations for its code changes. • 𝗧𝗮𝘀𝗸 𝗛𝗮𝗻𝗱𝗹𝗶𝗻𝗴: It performs better with established technologies like ReactJS but struggles with less popular tools. 𝗠𝗮𝗿𝗸𝗲𝘁 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 Devin is part of a competitive landscape where AI tools are rapidly evolving. The company behind Devin, Cognition Labs, recently raised $175 million at a $2 billion valuation, indicating significant investor interest despite the lack of revenue. 𝗖𝗼𝗻𝗰𝗹𝘂𝘀𝗶𝗼𝗻 While Devin presents an innovative solution for automating software development tasks, its reliance on Slack and the inherent limitations of AI-generated code raise questions about its practicality for all developers. Nonetheless, it represents a significant step forward in the integration of AI in software engineering.