Beyond working to block out safety and security-threatening prompt injection attacks, Microsoft has also introduced tooling to focus on the reliability of gen AI apps.
Join us in Atlanta on April 10th and explore the landscape of security workforce. We will explore the vision, benefits, and use cases of AI for security teams. Request an invite here. Yesterday, a new startup called Hume AI announced it had raised $50 million in a Series B round led by EQT Ventures with […]
We propose a notion of causal influence that describes the ‘intrinsic’ part of the contribution of a node on a target node in a DAG. By recursively writing each node as a function of the upstream noise terms, we separate the intrinsic information added by each node from the one obtained from its…
There are more than 8,500 performance results in the MLCommons' latest benchmark, testing all manner of combinations and permutations of hardware, software and AI inference use cases.
The selection of the assumed effect size (AES) critically determines the duration of an experiment, and hence its accuracy and efficiency. Traditionally, experimenters determine AES based on domain knowledge. However, this method becomes impractical for online experimentation services managing…
In this video presentation, our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, sits down with industry luminary Sebastian Raschka to discuss his latest book, Machine Learning Q and AI, the open-source libraries developed by Lightning AI, how to exploit the greatest opportunities for LLM development, and what’s on the horizon for LLMs.
Accenture's $1 billion investment in LearnVantage, an AI-powered learning platform, aims to bridge the growing skills gap and help businesses upskill their workforces to capitalize on emerging technologies like generative AI, cloud computing, and cybersecurity.
Generative Vision-Language Models (VLMs) are prone to generate plausible-sounding textual answers that, however, are not always grounded in the input image. We investigate this phenomenon, usually referred to as “hallucination” and show that it stems from an excessive reliance on the language…
E-commerce platforms typically store and structure product information and search data in a hierarchy. Efficiently categorizing user search queries into a similar hierarchical structure is paramount in enhancing user experience on e-commerce platforms as well as news curation and academic research.…
In Part II of VentureBeat's virtual interview, Krebs emphasizes the need for organizations to improve their infrastructure's cyber and physical security.
Kinetica, the real-time GPU-accelerated database for analytics and generative AI, unveiled at NVIDIA GTC its real-time vector similarity search engine that can ingest vector embeddings 5X faster than the previous market leader, based on the popular VectorDBBench benchmark.
The transformer is a powerful data-modeling framework responsible for remarkable performance on a wide range of tasks. However, transformers are limited in terms of scalability as it is suboptimal and inefficient to process long-sequence data. To this purpose we introduce BLRP (Bidirectional…
Active learning parallelization is widely used, but typically relies on fixing the batch size throughout experimentation. This fixed ap-proach is inefficient because of a dynamic trade-off between cost and speed—larger batches are more costly, smaller batches lead to slower wall-clock run-times—and…
Hitachi Vantara, the data storage, infrastructure, and hybrid cloud management subsidiary of Hitachi, Ltd. (TSE: 6501), today announced a collaboration with NVIDIA to create a new generation of transformational artificial intelligence (AI) solutions. Hitachi Vantara will develop a portfolio of solutions, Hitachi iQ, to drive targeted AI outcomes by layering industry-specific capabilities on top of its AI solution stack, so outcomes can be more specific and relevant to an organization’s business.