Microsoft’s BEiT-3 Foundation Model: A ‘Big Convergence of …
Aug 30, 2022 · In the new paper Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks, a Microsoft research team presents BEiT-3, a general-purpose state-of-the-art multimodal foundation model for both vision and vision-language tasks that advances the big convergence of backbone architectures, pretraining tasks, and model scaling.
Synced
Feb 18, 2024 · In a recent technical report, OpenAI introduces Sora, a groundbreaking text-to-video model. Sora stands out for its ability to generate videos and images spanning a wide range of durations, aspect ratios, and resolutions, producing up …
NeurIPS 2018 Opens; Best Papers Announced | Synced
Dec 3, 2018 · The 2018 Conference on Neural Information Processing Systems (NeurIPS) kicked off today in Montréal. In their opening remarks this afternoon the NeurIPS organizing committee announced the conference's major best paper selections and other awards. Four submissions shared top honors in the best paper category: Non-Delusional Q-Learning and Value-Iteration from researchers at Google AI: The paper
Google’s AMIE Marks A Significant Milestone Toward …
Jan 17, 2024 · The foundation of effective medical practice lies in the exchange between physicians and patients, where adept history-taking lays the groundwork for precise diagnosis, efficient management, and the establishment of enduring trust. Recent advancements in general-purpose large language models (LLMs) highlight the potential of artificial intelligence (AI) systems to plan, reason, and incorporate ...
Improving Image Matching: New Open-Source Benchmark with …
Apr 6, 2020 · In an ancient Indian parable, six blind men encounter an elephant but struggle to discern what it is. One taps the beast’s side, guessing it could be a wall. Gripping a leg, another imagines a tree trunk, while a third taps the pointy tusks and fears a threatening spear. Such challenges continue in contemporary computer
2020 in Review: 10 AI Failures | Synced
Jan 1, 2021 · Publication of Study Using AI to “Predict Criminality” Based on Faces Blocked by AI Researchers. In June, a controversial study by Harrisburg University in Pennsylvania, A Deep Neural Network Model to Predict Criminality Using Image Processing, proposed an automated facial recognition system the authors claimed could predict whether an individual is a criminal from a single photograph of ...
2020 in Review: 10 AI Papers That Made an Impact | Synced
Dec 17, 2020 · Much of the world may be on hold, but AI research is still booming. The volume of peer-reviewed AI papers has grown by more than 300 percent over the last two decades, and attendance at AI conferences continues to increase significantly, according to the Stanford AI Index.In 2020, AI researchers made exciting progress on applying transformers to areas other than natural-language processing ...
Matrix Multiplication-Free Language Models Maintain Top-Tier ...
Jun 9, 2024 · Matrix multiplication (MatMul) is a fundamental operation in most neural networks, primarily because GPUs are highly optimized for these computations. Despite its critical role in deep learning, MatMul operations are a significant source of computational expense, often consuming the bulk of execution time and memory access …
Stanford U & Google’s Generative Agents Produce Believable …
Apr 12, 2023 · In the new paper Generative Agents: Interactive Simulacra of Human Behavior, a team from Stanford University and Google Research presents agents that draw on generative models to simulate both individual and emergent group behaviours that are humanlike and based on their changing experiences and environment.
Yann LeCun Cake Analogy 2.0 | Synced
Feb 22, 2019 · Facebook AI Chief Yann LeCun introduced his now-famous “cake analogy” at NIPS 2016: “If intelligence is a cake, the bulk of the cake is unsupervised learning, the icing on the cake is supervised learning, and the cherry on the cake is reinforcement learning (RL).”The quip rippled across the AI community and confirmed LeCun a strong advocate of unsupervised learning, a machine learning ...