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BREAKING NEWS: 𝗧𝗵𝗲 𝗔𝗜 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗶𝘀 𝗛𝗲𝗿𝗲: 𝗠𝗲𝗲𝘁 𝗗𝗲𝘃𝗶𝗻, 𝘁𝗵𝗲 𝗙𝗶𝗿𝘀𝘁 𝗧𝗿𝘂𝗲 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗪𝗼𝗿𝗸𝗲𝗿 Cognition Labs recently came into the limelight with the release of Devin, the world's first real digital worker. This is the game-changer in AI capabilities, which is going to revolutionize how corporations conduct business. What sets Devin apart is that it works on independent learning, reasoning, and completing most of the complex knowledge work there is in the world. From data analysis and copywriting to coding and customer service, there is not a sphere where Devin cannot stand up for you. Industry experts have actually been left in absolute awe by the potential that this technological breakthrough holds. Fueled by advanced natural language processing and computer vision, Devin is imbued with the powers of understanding and endowing communication that rivals any augmented human knowledge worker. But its endless working capacity, exceptional speed, and literally boundless scalability give an unfair advantage to even the highest-possible number of human workforces. The possibilities are endless as Devin continues learning new skills at an exponential rate. The data is clear, and from it emerges the likelihood: Devin is signaling the next frontier of how enterprise productivity and operational efficiency will be looked at. Companies deploying the real digital workers today, just the way Devin has been doing, would ensure they are the ones leading the market tomorrow, undisputed. More info: https://lnkd.in/ekdBEumt What can Devin do? Watch videos to get amazed: Devin can learn how to use unfamiliar technologies. After reading a blog post, Devin runs ControlNet on Modal to produce images with concealed messages for Sara. Devin can build and deploy apps end to end. Devin makes an interactive website which simulates the Game of Life! It incrementally adds features requested by the user and then deploys the app to Netlify. Devin can autonomously find and fix bugs in codebases. Devin helps Andrew maintain and debug his open source competitive programming book. And...more #ai #artificialintelligence #digitalworkforce #innovation 💠Excited about the future of AI? Let's start a conversation! 💠Share your thoughts, like this post if you're as amazed as us with Devin's capabilities 💠Don't forget to follow for more updates by subscribing to our newsletter: https://lnkd.in/eXM5dv3F. https://lnkd.in/eDMz-4qG

It's so annoying when you are hiring and you receive an AI written response 🤖 Do people really think that they would dodge and management won't know the difference between AI written content and human written content? 🤔 This actually eases the hiring process and helps filter the likes of these at the early stage of the hiring funnel. Please understand that the application form is the only opportunity for you to show that you are capable, talented and driven. A genuine and thoughtful application would only help you go up the ladder of the hiring funnel. Everyone must first make an attempt to understand the question asked, spend some time reflecting and researching and then answer it. 🧠 Muiz Tariq

LLMs represent a high-dimensional function approximation—mapping natural language inputs to highly structured outputs. These models, while powerful, need to be composed into agents that can sequence tasks, infer dependencies, and make decisions autonomously. Artifact AI's architecture applies the principles of reinforcement learning, where reward maximization is tied to correct task execution, optimizing workflows over time. We use contextual embeddings as state representations, enabling the model to understand sequences of actions, their constraints, and dependencies. While LLMs are theoretically powerful, their practical business value emerges when composed within an agentic framework. At the application layer, our autonomous agents handle tasks that usually require significant human intervention. 🚀 At Artifact AI, we're hiring! 🧠 If you love solving some of the most mathematically complex challenges in AI/ML, please reach out to me directly!

DVA is not associated with this job posting Staff Machine Learning Engineer, Content Understanding USA https://lnkd.in/gP8rwC-Q What you’ll do: Utilize state of the art machine learning, natural language processing, and multimodal modeling techniques to build content signals that power personalized product experience across Pinterest ecosystems (discovery, growth, ads etc). Gather, examine, and integrate findings from data to build effective data-driven models. Partner with surface engineering teams and product team to discover opportunities to improve recommendation on Pinterest through content/user understanding. Drive team level tech strategy, and solve complex problems independently. What we’re looking for: MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related fields. 5+ years of industry experience in machine learning in industry and 1+ years of TL in use cases with large scale: content understanding, recommendation systems, information retrieval. Experience with Generative AI and LLM. Hands-on experience working with large scale ML modeling development and productization. Effective collaborator working with cross functional partners and an excellent communicator. #innovation #management #digitalmarketing #technology #creativity #futurism #startups #marketing #socialmedia #socialnetworking #motivation #personaldevelopment #jobinterviews #sustainability #personalbranding #education #productivity #travel #sales #socialentrepreneurship #fundraising #law #strategy #culture #fashion #business #networking #hiring #health #inspiration

When it comes to recruitment, manual screening and AI screening both have their pros and cons. But one of them is clearly winning 🏆 Check out the comparison and see why ProjectFitter is the future of hiring: https://projectfitter.ai/

🚀 This is such a timely and insightful post, Daniel! The emphasis on LLM and generative AI concepts in interviews reflects how rapidly the field is evolving. The topics you’ve highlighted—like transformer architecture, RAG, and multi-modal models—are not just essential for acing interviews but also for understanding the backbone of modern AI systems. 💡 Distributed inference and training and embedding techniques are particularly important as they directly influence the scalability and efficiency of deploying LLMs in real-world applications. It’s exciting to see companies like Meta, OpenAI, and Google at the forefront of these advancements, offering opportunities for engineers to work on cutting-edge technologies. 🎯 Your bootcamps and prep resources look like an amazing way for aspiring ML engineers to level up. Breaking into the field can feel daunting, but having structured guidance like this can make all the difference for candidates looking to land their dream roles. 🔥 Thanks for sharing this valuable list—it’s a great reminder of where the industry is headed and what aspiring AI professionals should focus on to stay ahead of the curve. Definitely bookmarking this! #LLM #GenerativeAI #MachineLearning #CareerInAI 👏🔗

📝 Revolutionize Your Recruitment with AI-Powered Job Descriptions As a talent expert at NVIDIA, I've discovered a game-changing tool for creating compelling job postings: Copywriter GPT. Here's how you can leverage this AI assistant to streamline your hiring process: 1. Access Copywriter GPT (link in comments) 2. Choose a template (e.g., "Senior Software Engineer") 3. Input key requirements (like "5+ years in Python and ML") 4. Generate content with one click 5. Refine to match your company's voice 6. Publish and share across platforms In minutes, you'll have a professional, engaging job description ready to attract top talent. Have you tried AI-assisted recruiting yet? Share your experiences or questions below! #TalentAcquisition #AIinHR #RecruitmentInnovation #TechHiring

🚀 Excited to share this click-worthy blog post on AI Chatbots in Customer Support: Breaking Down the Myths! You don't want to miss out on debunking the misconceptions around chatbots and discovering how they enhance human support. Dive into the insightful read here: via Code Like A Girl - Medium. CLAG #AI #CustomerSupport #TechTrends

"I was so productive today..." Meanwhile... Soon AI will be in every household. That's the end game for productivity. But there's a big challenge... 👇 Moving beyond next-word prediction to true reasoning. AI that thinks. 👀 The core problem? Most LLMs are impressive but fundamentally flawed. They predict what word comes next based on training data. This creates "salience" - amazing when it works, but prone to hallucination. How we're trying to solve it at Redcar.io" We built an AI Agent Platform that adds traditional engineering rigor on top of foundation models. The technical architecture: 1) Multi-source verification engine 2) Reasoning framework 3) Context management system 📌 Real world sales example for you: When qualifying B2B leads, our system: → Constructs company knowledge graphs → Validates data across multiple sources → Applies industry-specific reasoning → Self-monitors for accuracy → Auto-corrects when confidence is low ✨ The results? Our agents consistently outperform raw GPT-4 on specialized tasks. We're seeing significantly reduced hallucination rates. And most importantly - reliable, consistent output. 👋 P.S. We're hiring founding engineers! → Full Stack Engineer → Applied AI Engineer h/t Matt Tuck for this meme btw 😂

Interesting opportunities