OpenAI and Los Alamos National Laboratory are working to develop safety evaluations to assess and measure biological capabilities and risks associated with frontier models.

Engineering and running experiments are a key component of most PhDs in AI. While there are plenty of more theoretical topics that are often limited to smaller scale experimentation, the trend has definitely been to scale up models, datasets and experiments. Thus, being an effective engineer and setting up experiments in an efficient way can be a crucial element of being successful during a PhD. In this article, I want to share some lessons I learned on effective experimentation. The post The Importance of Effectively Experimenting in an AI PhD appeared first on David Stutz.

Vision-Language Models Booming. PaliGemma. Phi-3 Vision. Florence-2. LLaVA-NeXT. ML in Video games. PCA in Latent Space. MosaicML Agents Framework. MoEs at Scale. GraphRAG. Image SSL on a Shoestring.

Rethinking AI agent benchmarking and evaluation

Prompt Engineering 2.0. Automated Prompt Optimisation. AI Scaling Myths. AGI World Models. What's an AI Agent? GenAI at LinkedIn. Failed AI Projects. Img2Txt2Txt Models. RAGFlow. JEPA Deep Dive.

Scaling will run out. The question is when.

CriticGPT, a model based on GPT-4, writes critiques of ChatGPT responses to help human trainers spot mistakes during RLHF

We’re partnering with TIME and its 101 years of archival content to enhance responses and provide links to stories on Time.com

AI and While You Were Out IRL. DeepSeek Coder v2. Hermes2+Theta Llama-3 70B. Unique 3D. AutoIF. Infinity Instruct. Florence. Claude 3.5 onnet. Claudette. Agile RL. TexGrad. PlanRAG.

OpenAI Acquires Rockset

Highlighting innovative research and AI integration in cybersecurity

We present a holistic approach to building a robust and useful natural language classification system for real-world content moderation.

Diffusion models have significantly advanced the fields of image, audio, and video generation, but they depend on an iterative sampling process that causes slow generation.

Consistency models are a nascent family of generative models that can sample high quality data in one step without the need for adversarial training.

Paf adopted ChatGPT Enterprise across its entire company, with engineers using custom GPTs on a daily basis to speed up routine development tasks. Paf also integrated ChatGPT Enterprise into the grit:lab coding academy (gritlab.ax), training the next generation of software developers using an AI-augmented, systems-architecture mindset from day one. In addition to the wide range of use cases for developers and grit:lab students, 70% of Paf employees actively use ChatGPT Enterprise, spanning business teams like finance, HR, marketing, and customer support.

Color Health is working with OpenAI to pioneer a new way of accelerating cancer patients’ access to treatment. Their new Cancer Copilot application uses GPT-4o to identify missing diagnostics and create tailored workup plans, enabling healthcare providers to make evidence-based decisions about cancer screening and treatment.

Compound AI Systems, Txt2SQL & Data Agents. On Apple Intelligence Models. Lessons Building AI Agents. NVIDIA Nemotron-4 340B. New Memory Tuning. agentUniverse. Let's Reproduce GPT-2. Mixture of Agents

Writing up results from a recent project

Achieving even more surgical edits than LEACE without concept labels at inference time.