Grigory SapunovGPT-4V is coming!The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)Oct 5, 2023Oct 5, 2023
Grigory SapunovLLMs and a possible future for SearchThe recent surge of Generative AI has pushed the boundaries of what was previously thought possible.Dec 22, 20221Dec 22, 20221
Grigory SapunovOpenAI and the road to text-guided image generation: DALL·E, CLIP, GLIDE, DALL·E 2 (unCLIP)Let’s look at the evolution of text-guided image generation models from OpenAI, as there are more datapoints than just DALL·E and DALL·E 2.May 1, 20221May 1, 20221
Grigory SapunovFoundation ModelsIn August 2021 Stanford announced establishing the Center for Research on Foundation Models (CRFM) as part of the Stanford Institute for…Nov 22, 2021Nov 22, 2021
Grigory SapunovHardware for Deep Learning. Part 4: ASICThis is a part about ASICs from the “Hardware for Deep Learning” series. The content of the series is here.Jan 12, 20211Jan 12, 20211
Grigory SapunovJAXJAX by Google Research is getting more and more popular. Deepmind recently announced they are using JAX to accelerate their research and…Dec 20, 20201Dec 20, 20201
Grigory SapunovGPT-3: Language Models are Few-Shot LearnersOpenAI just published a paper “Language Models are Few-Shot Learners” presenting a recent upgrade of their well-known GPT-2 model — the…Jun 2, 2020Jun 2, 2020
Grigory SapunovFP64, FP32, FP16, BFLOAT16, TF32, and other members of the ZOOThere are many floating point formats you can hear about in the context of deep learning. Here is a summary of what are they about and…May 16, 20202May 16, 20202
Grigory SapunovAdaptive Computation Time (ACT) in Neural Networks [3/3]Part 3: ACT in TransformersJan 7, 2020Jan 7, 2020
Grigory SapunovAdaptive Computation Time (ACT) in Neural Networks [2/3]Part 2: ACT in Residual NetworksJan 3, 2020Jan 3, 2020