David Shamma’s Post

Generative AI Tops Highest-Paying Tech Skill List | Careers | Communications of the ACM: In 2023, 30% of computer science jobs were AI-related, according to a Biz Report survey. Generative AI was identified as the highest-paid technology skill in Indeed's 2024 Workforce Insights Report, with an average annual salary of $174,727. Other top skills included system-on-chip, deep learning, Torch, PyTorch, computer vision, SystemVerilog, Mesos, Rust, and Elixir. These skills are in demand for positions such as data scientists, machine learning engineers, software engineers, and research scientists.

Evolving Roles: From ML Scientists to ML Engineers 🌱🔧 Within the AI, a fascinating transition happened. It all starts with the ML Scientists. 𝙈𝙇 𝙎𝙘𝙞𝙚𝙣𝙩𝙞𝙨𝙩𝙨 - 𝙏𝙝𝙚 𝙋𝙞𝙤𝙣𝙚𝙚𝙧𝙨: In the early days, ML Scientists were the trailblazers. They delved into uncharted territories, experimenting with algorithms and unravelling the intricacies of data. Their mission was to explore the unknown and lay the theoretical groundwork for machine learning. Think Hinton and Lecun. 𝙏𝙧𝙖𝙣𝙨𝙛𝙤𝙧𝙢𝙖𝙩𝙞𝙤𝙣 𝙞𝙣𝙩𝙤 𝙈𝙇 𝙀𝙣𝙜𝙞𝙣𝙚𝙚𝙧𝙨: As AI matured, the need for practical implementation became evident. This shift birthed the role of ML Engineers. These experts take the theories crafted by ML Scientists and turn them into functional reality. They build the infrastructure, optimize algorithms, and ensure models operate seamlessly in real-world settings. 𝘼 𝙎𝙚𝙖𝙢𝙡𝙚𝙨𝙨 𝘾𝙤𝙣𝙩𝙞𝙣𝙪𝙪𝙢: This evolution isn't a break but a seamless continuum. ML Scientists laid the foundation, and ML Engineers built upon it, bridging the gap between theory and application. Together, they form the pillars that uphold the AI landscape. And, of course, we're currently hiring both ML engineers and scientists at the European Centre for Medium-Range Weather Forecasts. Leave your comment below if you're interested! #AIevolution #TechRoles #MLScientistsToEngineers

Can anyone be a Prompt Engineer? I just watched this amazing video by Joanna Stern from WSJ, where she interviews Swetha Revanur, the Head of Technical Staff at Hebbia AI. Swetha explains what prompt engineering is, how it works, and why it is a crucial skill for anyone working with LLM AI models. Prompt engineering is the art of creating effective prompts that guide the LLM AI models to generate the desired outputs. It requires creativity, attention to detail, and an understanding of the model’s behavior. Swetha demonstrates how Hebbia AI uses prompt engineering to create powerful AI workflows for the modern firm, enabling clients to make decisions 10x more confidently and quickly. Kudos to Swetha and George Sivulka, the CEO of Hebbia AI.

Transforming Compliance: Discover Simply Regulation - FinregE's Innovative Regtech Solutions! 🚀✅ Join us as we redefine the approach to financial services laws and regulations with our groundbreaking machine learning and natural language processing technologies. 🌐💡 Our exceptional team of experts, including data scientists, software engineers, and compliance professionals, collaborate to deliver cutting-edge solutions that tackle compliance challenges head-on. 🙌🔬 Visit our website now to learn how FinregE can help your business achieve seamless compliance. 👉🔎 #RegtechRevolution #ComplianceSolutions #IndustryLeaders #DataScienceExperts"

Transformers have been driving performance in #LLMs, but they can’t scale to long context. Researchers at Carnegie Mellon University and Princeton University are releasing Mamba, a structured state space model (#ssm) architecture that can beat Transformers in language modeling, with linear scaling and up to 5x higher inference throughput. Impressive...and something to watch. https://lnkd.in/d54CHGMU

From quantum computing to machine learning, there’s a world of skills and roles available in deep tech. We talked to Ian Storey of Hays about what you need to know to work in the industry. #DeepTechWeek #DeepTech #QuantumComputing #MachineLearning

𝗪𝗵𝘆 𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗶𝘀 𝘁𝗵𝗲 𝗡𝗲𝘅𝘁 𝗕𝗶𝗴 𝗧𝗲𝗰𝗵 𝗥𝗼𝗹𝗲! 🤖 Just like you, I've also been swept off by the #GenAI wave. I spent the last couple of months knee-deep in understanding developments in the AI space, evaluating use cases, and analyzing trends. After developing a dozen chatbots, engineering prompts to succumb to my demands, and building several RAG pipelines, I've come to realize how the native engineering tech roles are undergoing a massive shift. Double-clicking on this epiphany, I recorded a video for why #AI #Engineer is going to be the next big tech role. - What does the trend look like? - Who are AI Engineers? - How are they different from AI Researchers? - Why do we need them? - And why you should start NOW! #AIEngineer #MachineLearning #AIEngineering #DataScience #ArtificialIntelligence #Technology #NLP All covered in this video: 🎥👨💻

I have something embarrassing to admit. When I was in college, at one point I got super excited about the new "superpowers" I was getting. I could solve problems using computers, math, and probability. It became easy to see every problem as a computational one that could be solved through modeling, deduction, and inference. And for a little while, I thought that was the case. This is a typical case of 𝐭𝐞𝐜𝐡𝐧𝐨-𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐬𝐦. The idea that every problem can be solved by reduction to a technological one. We're seeing this happening a lot these days. CEOs claiming that some new technology, say generative AI, is "all you need" to do people's jobs and solve pretty much anything. With experience, you learn what's out of the reach of your technological tools. Or what other, non-technological expertise you need to bring on board to solve real problems. So if you're learning a new technology, a good measure of your expertise is not just what you know how to do. But your knowledge of limitations and of how that technology interacts with its environment when deployed in the real world.

Discover hiring trends for AI Talent, such as the current landscape for AI Engineers, Top Industries hiring for AI Engineers, Labor market dynamics, Top skills in demand for AI engineers, Skills needed for AI engineers, and Talent strategies to build strong pipelines for AI engineers. 💡 Knowledge is power - this is a great read regarding the hiring landscape in the AI space. https://lnkd.in/eP_69DCt