Customers tell us they see great potential in using large language models (LLMs) with their data to improve customer experiences, automate internal processes, access and find information, and create new content —just to name a few of the emerging generative AI use cases. There are many ways to leverage your data, so in this blog, …
Read more “To tune or not to tune? A guide to leveraging your data with LLMs”
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Noise-canceling headphones are a godsend for living and working in loud environments. They automatically identify background sounds and cancel them out for much-needed peace and quiet. However, typical noise-canceling fails to distinguish between unwanted background sounds and crucial information, leaving headphone users unaware of their surroundings.
DALL-E illustration showcasing my audio demos and conversations with GPT-4o This week, OpenAI announced the release of GPT-4o, the latest iteration of its language model with new capabilities across multiple modalities. The “o” in GPT-4o stands for “omni,” highlighting its enhanced ability to reason in real-time across audio, vision, and text. This makes it especially useful for …
Large Language Model or LLM inference has two phases, the prompt (or prefill) phase to output the first token and the extension (or decoding) phase to the generate subsequent tokens. In this work, we propose an efficient parallelization scheme, KV-Runahead to accelerate the prompt phase. The key observation is that the extension phase generates tokens …
Read more “KV-Runahead: Scalable Causal LLM Inference by Parallel Key-Value Cache Generation”
Business leaders risk compromising their competitive edge if they do not proactively implement generative AI (gen AI). However, businesses scaling AI face entry barriers. Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges. According to International Data Corporation (IDC), stored data is set to increase by …
Read more “The power of remote engine execution for ETL/ELT data pipelines”
Crafting new questions for exams and quizzes can be tedious and time-consuming for educators. The time required varies based on factors like subject matter, question types, experience level, and class level. Multiple-choice questions require substantial time to generate quality distractors and ensure a single unambiguous answer, and composing effective true-false questions demands careful effort to …
Developers and engineers face several major challenges when scaling AI/ML workloads. One challenge is getting access to the AI infrastructure they need. AI/ML workloads require a significant amount of computational resources, such as CPUs and GPUs. Developers need to have sufficient resources to run their workloads. Another challenge is handling the diverse patterns and programming …
Read more “Announcing general availability of Ray on Vertex AI”
A collaboration between NVIDIA and academic researchers is prepping robots for surgery. ORBIT-Surgical — developed by researchers from the University of Toronto, UC Berkeley, ETH Zurich, Georgia Tech and NVIDIA — is a simulation framework to train robots that could augment the skills of surgical teams while reducing surgeons’ cognitive load. It supports more than …
Read more “Needle-Moving AI Research Trains Surgical Robots in Simulation”
A team of researchers has developed a drone that flies autonomously using neuromorphic image processing and control based on the workings of animal brains. Animal brains use less data and energy compared to current deep neural networks running on GPUs (graphic chips). Neuromorphic processors are therefore very suitable for small drones because they don’t need …
Read more “Animal brain inspired AI game changer for autonomous robots”