How to Redefine Your ABM Playbook Using AI
Explore key takeaways from our recent webinar on how AI can transform ABM strategies with workflow automation, personalization at scale, and more.
Explore key takeaways from our recent webinar on how AI can transform ABM strategies with workflow automation, personalization at scale, and more.
Generative AI applications are gaining widespread adoption across various industries, including regulated industries such as financial services and healthcare. As these advanced systems accelerate in playing a critical role in decision-making processes and customer interactions, customers should work towards ensuring the reliability, fairness, and compliance of generative AI applications with industry regulations. To address this …
Foundation models such as Gemini have revolutionized how we work, but sometimes they need guidance to excel at specific business tasks. Perhaps their answers are too long, or their summaries miss the mark. That’s where supervised fine-tuning (SFT) comes in. When done right, it unlocks incredible precision to tailor Gemini for specialized tasks, domains, and …
Read more “Supervised Fine Tuning for Gemini: A best practices guide”
According to Meta, memory layers may be the the answer to LLM hallucinations as they don’t require huge compute resources at inference time.Read More
According to Mark Zuckerberg, Meta trust and safety workers will be relocated to Texas to prevent them from “censoring” users. Experts point to other advantages.
EPFL researchers have developed 4M, a next-generation, open-sourced framework for training versatile and scalable multimodal foundation models that go beyond language.
With large language model (LLM) products such as ChatGPT and Gemini taking over the world, we need to adjust our skills to follow the trend.
Researchers have harnessed artificial intelligence to take a key step toward slashing the time and cost of designing new wireless chips and discovering new functionalities to meet expanding demands for better wireless speed and performance.
We introduce Shape Tokens, a 3D representation that is continuous, compact, and easy to integrate into machine learning models. Shape Tokens serve as conditioning vectors, representing shape information within a 3D flow-matching model. This flow-matching model is trained to approximate probability density functions corresponding to delta functions concentrated on the surfaces of 3D shapes. By …
Part 2: Navigating Ambiguity By: Varun Khaitan With special thanks to my stunning colleagues: Mallika Rao, Esmir Mesic, Hugo Marques Building on the foundation laid in Part 1, where we explored the “what” behind the challenges of title launch observability at Netflix, this post shifts focus to the “how.” How do we ensure every title launches seamlessly …