NVIDIA and key partners today announced the availability of new products and services featuring the NVIDIA H100 Tensor Core GPU — the powerful GPU for AI — to address rapidly growing demand for generative AI training and inference.
Heard on the Street – 3/20/2023
Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
How AI Helps Prevent Human Error In Data Analytics
In this contributed article, April Miller, a senior IT and cybersecurity writer for ReHack Magazine, discusses how AI can help limit human error and improve data analysis accuracy. Explore how AI is fixing human error in data analytics and revolutionizing how we approach this critical field.
Video Highlights: GPT-4 Developer Livestream
Here is Greg Brockman, President and Co-Founder of OpenAI, for a March 14, 2023 developer demo showcasing GPT-4 and some of its capabilities/limitations. Included are a number of very compelling new use case capabilities over the previous GPT-3.5 version.
Don’t overlook independence in Responsible AI
In this contributed article, Dr Stuart Battersby, Chief Technology Officer of Chatterbox Labs, has the aim to raise awareness of a key issue in the field of Responsible AI (aka Ethical AI or Trustworthy AI), and that is the issue of independence.
Research Highlights: Real or Fake Text? We Can Learn to Spot the Difference
A team of researchers at the University of Pennsylvania School of Engineering and Applied Science is seeking to empower tech users to mitigate risks of AI generated misinformation. In a peer-reviewed paper presented at the February 2023 meeting of the Association for the Advancement of Artificial Intelligence, the authors demonstrate that people can learn to spot the difference between machine-generated and human-written text.
Lightning AI Releases PyTorch Lightning 2.0 and a New Open Source Library for Lightweight Scaling of Machine Learning Models
Lightning AI, the company accelerating the development of an AI-powered world, today announced the general availability of PyTorch Lightning 2.0, the company’s flagship open source AI framework used by more than 10,000 organizations to quickly and cost-efficiently train and scale machine learning models. The new release introduces a stable API, offers a host of powerful features with a smaller footprint, and is easier to read and debug.
Data Science Bows Before Prompt Engineering and Few Shot Learning
In this contributed article, editorial consultant Jelani Harper takes a new look at the GPT phenomenon by exploring how prompt engineering (stores, databases) coupled with few shot learning can constitute a significant adjunct to traditional data science.
TOP 10 insideBIGDATA Articles for February 2023
In this continuing regular feature, we give all our valued readers a monthly heads-up for the top 10 most viewed articles appearing on insideBIGDATA. Over the past several months, we’ve heard from many of our followers that this feature will enable them to catch up with important news and features flowing across our many channels.
Challenges for Startups in Adopting AI and Data Analytics
In this contributed article, Bal Heroor, CEO and Principal at Mactores, believes that by 2027, it is nearly unavoidable that every business, both big and small, will need to get serious about adopting a high-value data analytics system. While this can be a costly investment, there’s no reason that even a startup can’t be a part of the data transformation that is affecting almost every industry sector today.