When starting their AI initiatives, many companies are trapped in silos and treat AI as a purely technical enterprise, sidelining domain experts or involving them too late. They end up with generic AI applications that miss industry nuances, produce poor recommendations, and quickly become unpopular...
AGI in 2025 |Do you think what matters today will still matter in the coming months? TL;DR: No!
OpenAI, Sam Altman, Elon Musk, xAI, Anthropic, Gemini, Google, Apple… all these companies are racing to build AGI by 2025, and once achieved, it will be replicated by dozens of others within weeks. The idea of creating a compressed knowledge base of humanity, extracting information, and iterating on...
Beyond DeepSeek: An Overview of Chinese AI Tigers and Their Cutting-Edge Innovations
The recent disruption caused by DeepSeek’s R1 model sent shockwaves through the AI community, demonstrating that Chinese AI advancements may have been underestimated. The model’s performance, rivaling some of the most advanced offerings from OpenAI and Anthropic at a fraction of the cost, signaled a...
When I talk to corporate customers, there is often this idea that AI, while powerful, won’t give any company a lasting competitive edge. After all, over the past two years, large-scale LLMs have become a commodity for everyone. I’ve been thinking a lot about how companies can shape a competitive adv...
AlignmentDec 18, 2024Alignment faking in large language modelsThis paper provides the first empirical example of a model engaging in alignment faking without being trained to do so—selectively complying with training objectives while strategically preserving existing preferences.
AlignmentDec 18, 2024Alignment faking in large language modelsThis paper provides the first empirical example of a model engaging in alignment faking without being trained to do so—selectively complying with training objectives while strategically preserving existing preferences.
We are proud to introduce the {mall} package. With {mall}, you can use a local LLM to run NLP operations across a data frame. (sentiment, summarization, translation, etc). {mall} has been simultaneously released to CRAN and PyPi (as an extension to Polars).
An overview of classifier-free diffusion guidance: impaired model guidance with a bad version of itself (part 2)
How to apply classifier-free guidance (CFG) on your diffusion models without conditioning dropout? What are the newest alternatives to generative sampling with diffusion models? Find out in this article!
Be Part of the AI Revolution at the Chatbot Conference Tomorrow!
Tomorrow, September 24, 2024, San Francisco will host one of the biggest global AI events of the year: the Chatbot Conference! Whether you’re passionate about artificial intelligence, curious about chatbots, or simply eager to connect with industry leaders, this conference is for you.Why You Should ...
🚀 What to ExpectThe conference features a range of events designed to enrich attendees’ understanding of the chatbot industry:Expert Keynotes: Get insights from industry leaders at the forefront of AI innovation.Workshops: These certified workshops provide hands-on experience, helping participants d...
Limited Time Offer: Get Your Exclusive Online Passes to the Chatbot Conference — Act Fast!
🚀 Limited Time Offer: Get Your Exclusive Online Passes to the Chatbot Conference — Act Fast! 🚀Exciting news ahead! With an incredible surge of enthusiasm, we're rolling out an exclusive Online Only option for this year's Chatbot Conference, kicking things off with an absolutely phenomenal launch!Tod...
An overview of classifier-free guidance for diffusion models
Learn more about the nuances of classifier-free guidance, the core sampling mechanism of current state-of-the-art image generative models called diffusion models.
We are thrilled to introduce {keras3}, the next version of the Keras R package. {keras3} is a ground-up rebuild of {keras}, maintaining the beloved features of the original while refining and simplifying the API based on valuable insights gathered over the past few years.
Interact with Github Copilot and OpenAI's GPT (ChatGPT) models directly in RStudio. The `chattr` Shiny add-in makes it easy for you to interact with these and other Large Language Models (LLMs).
Understanding Vision Transformers (ViTs): Hidden properties, insights, and robustness of their representations
We study the learned visual representations of CNNs and ViTs, such as texture bias, how to learn good representations, the robustness of pretrained models, and finally properties that emerge from trained ViTs.