NVIDIA

SEPTEMBER 19, 2023

helps developers and researchers streamline and accelerate the training of AI for production. team, Boehmer uses Blender and Adobe Substance Painter to design 3D assets with high levels of physical accuracy and photorealism, helping ensure that synthetic data can be used to efficiently train AI models. As part of the SORDI.ai

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NVIDIA

NOVEMBER 15, 2023

With previous architectures, developers could train and test these layers independently, as they were governed by different models. To address this challenge, NVIDIA is bringing state-of-the-art sensor simulation pipelines used in DRIVE Sim and Isaac Sim to Omniverse Cloud on Microsoft Azure.

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NVIDIA

OCTOBER 26, 2023

The team has been training detection models for both audio and video input to track creatures. The tracking is initialized using targets detected by a fish detection neural network trained on open-source datasets for fish detection, which is fine-tuned with transfer learning from images gathered by CUREE. “We

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Marktechpost

FEBRUARY 21, 2024

Although their work has some limitations, like computationally expensive training and lack of elegantly handling duplicated objects, it still outperforms many previous methods across different metrics, and it demonstrates the capabilities of self-supervised learning in bridging the sim-to-real gap. Check out the Paper.

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Google Research AI blog

AUGUST 21, 2023

Sainath , Pedro M. Zih-Ching Chen, Chao-Han Huck Yang*, Bo Li , Yu Zhang , Nanxin Chen , Shuo-yiin Chang , Rohit Prabhavalkar, Hung-yi Lee, Tara N.

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Google Research AI blog

APRIL 13, 2023

Our robotic system combines scalable deep RL from real-world data with bootstrapping from training in simulation and auxiliary object perception inputs to boost generalization, while retaining the benefits of end-to-end training, which we validate with 4,800 evaluation trials across 240 waste station configurations.

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Google Research AI blog

APRIL 7, 2023

By leveraging a new stochastic differential equation (SDE) simulator of the wiping task to train the RL policy for high-level planning, the proposed end-to-end approach avoids the need for task-specific training data and is able to transfer zero-shot to hardware. We then use these “thresholded” images as the input to the RL policy.

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NVIDIA

MAY 28, 2023

Pegatron uses NVIDIA Isaac Sim , a robotic simulator, to program robotic arms in simulation and to model the performance of its fleets of mobile robots. Tapping into NVIDIA Omniverse Replicator provides synthetic data generation to simulate defects, helping build massive training datasets with domain randomization and other techniques.

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Marktechpost

JUNE 10, 2023

Large text-to-video models trained on internet-scale data have shown extraordinary capabilities to generate high-fidelity films from arbitrarily written descriptions. With the help of a Video Adapter, a massive pre-trained model can take on the visual aesthetic of a diminutive Sci-Fi animation model.

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NVIDIA

OCTOBER 5, 2023

Just as athletes train for a game or actors rehearse for a performance, surgeons prepare ahead of an operation. Dr. Cohen-Gadol, also a professor of neurological surgery at Indiana University School of Medicine, estimates that more than 90% of brain surgery training programs in the U.S. — Subscribe to NVIDIA healthcare news.

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NVIDIA

OCTOBER 18, 2023

Generative AI offers zero-shot learning — the ability for a model to recognize things specifically unseen before in training — with a natural language interface to simplify the development, deployment and management of AI at the edge.

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NVIDIA

MAY 28, 2023

Cloud-native tools for record, upload and replay enable easy debugging, map creation, training and analytics. Finally, Isaac AMR simplifies robot operations by tapping into physics-based simulation from Isaac Sim, powered by NVIDIA Omniverse , an open development platform for industrial digitalization.

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Allen AI

APRIL 5, 2023

As robots become increasingly integrated into our daily lives, it is important to ensure that they are trained to operate in real-world environments. That’s where Phone2Proc comes in — a new approach for generating a distribution of training environments that closely match the real-world physical space we are interested in.

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NVIDIA

SEPTEMBER 12, 2023

DeepScenario showed how it’s using NVIDIA hardware for training and inference on its AI models. The company plans to bring this NVIDIA-powered solution to the European market and expand beyond later next year.

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Unite.AI

AUGUST 28, 2023

While most AI-driven platforms are bounded by their pre-trained knowledge, BabyAGI stands out for its ability to adapt and learn from experiences. Westworld's interactive sandbox environment, reminiscent of The Sims, brings to life a town populated by generative agents.

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Google Research AI blog

FEBRUARY 14, 2023

In i-Sim2Real , we showed an approach to address the sim-to-real gap and learn to play table tennis with a human opponent by bootstrapping from a simple model of human behavior and alternating between training in simulation and deploying in the real world. In each iteration, both the human behavior model and the policy are refined.

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NVIDIA

JUNE 29, 2023

And the latest simulators can generate datasets to be used to train machine learning models that will run on the physical robots. Some simulators — such as NVIDIA Isaac Sim , an application built on NVIDIA Omniverse — can also provide physically accurate visualizations of the simulator output at each timestep.

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Bugra Akyildiz

DECEMBER 18, 2022

Contrastive learning describes a set of techniques for training deep networks by comparing and contrasting the models' representations of data. However, the bi-encoder trained on the description performs worse than lexical baselines.

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NVIDIA

MAY 15, 2024

ORBIT-Surgical — developed by researchers from the University of Toronto, UC Berkeley, ETH Zurich, Georgia Tech and NVIDIA — is a simulation framework to train robots that could augment the skills of surgical teams while reducing surgeons’ cognitive load.

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AWS Machine Learning Blog

MAY 5, 2023

FiftyOne by Voxel51 is an open-source toolkit for curating, visualizing, and evaluating computer vision datasets so that you can train and analyze better models by accelerating your use cases. You might train a general-purpose model or fine-tune a model to each user’s unique style with some form of feedback. Or something else?

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NVIDIA

MAY 23, 2023

The interface offers nonprogrammers a more “drag-and-drop” experience for programming and deploying robots, whether working directly on the factory floor with real robots on a tablet device or with access to simulation from Isaac Sim , powered by NVIDIA Omniverse. Learn more about NVIDIA Isaac Sim , Jetson Orin , Omniverse Enterprise.

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Marktechpost

NOVEMBER 29, 2023

The student vision policy network has been trained to address these limitations and has demonstrated minimal generalization gaps across datasets. To overcome these limitations, a controller was trained through reinforcement learning in simulation and successfully demonstrated real-world generalization to new shapes.

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Google Research AI blog

MAY 3, 2023

We introduce a learning-based indoor-to-outdoor transfer algorithm that uses deep reinforcement learning to train a navigation policy in simulated indoor environments, and successfully transfers that same policy to real outdoor environments. Specifically, we randomly tilt the simulated camera on the robot during training.

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AWS Machine Learning Blog

MAY 8, 2024

Prepaid services dominate the market, and multi-SIM usage is widespread. The model was trained on demographic, network usage, and network outage data from across the organization. The training pipeline is responsible for developing the base model, which is a CatBoost model trained on a comprehensive set of features.

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Unite.AI

APRIL 11, 2024

Another example of LLM agents interacting with the visual environment can be experienced in another online game, The Sims where agents have demonstrated remarkable success in social interactions and exhibit behavior that resembles humans.

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NVIDIA

MAY 28, 2023

It will use four DGX GH200 systems linked with NVIDIA Quantum-2 InfiniBand networking to supercharge data throughput for training large AI models. Then, content from generative AI tools trained on responsibly sourced data and built with NVIDIA Picasso will let them quickly produce virtual sets.

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PyImageSearch

SEPTEMBER 18, 2023

SAM and CLIP Integration As we briefly discussed in the previous tutorial, the CLIP model is a recent foundational model for computer vision that utilizes large-scale web-based image-text data to train strong representations that encode semantic knowledge. without using any data to train the model). as detailed in this tutorial.

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ODSC - Open Data Science

APRIL 27, 2023

With 8+ tracks featuring hands-on training sessions, workshops, and talks on essential data science and AI topics, ODSC East 2023 is the conference for building the skills you need to help shape the future with AI. What are the benefits of this technology, and how can you apply it?

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Google Research AI blog

MAY 26, 2023

Learning agile locomotion skills The Barkour benchmark features a diverse set of obstacles and a delayed reward system, which pose a significant challenge when training a single policy that can complete the entire obstacle course. We deploy both the specialist and generalist policies to hardware (zero-shot sim-to-real).

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Ines Montani

DECEMBER 14, 2023

I recommend getting a cheap pre-paid (e)SIM just for mobile data. If you’re desperate, there’s an exception for supermarkets at long-distance train stations, for example Ostbahnhof or Central Station. Drinking on the subway is not officially allowed, but common and tolerated. Sundays : Shops and supermarkets are closed on Sundays.

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Viso.ai

MAY 1, 2024

have already created System in-module (SiM), with a lot of System-on-Chip (SoC) components. Deployment in Homes As the Stick device collected data, the researchers prepared the dataset and developed the algorithm to tune the pre-trained model. Stanford Roadmap Paper for Home Robots – Source Chip producers (Nvidia, Qualcomm, etc.)

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BAIR

APRIL 6, 2023

training of large models) to the cloud via the Internet. The systems aspect of IFL is another compelling research direction: recent developments in cloud and fog robotics enable robot fleets to offload all supervisor allocation, model training, and crowdsourced teleoperation to centralized servers in the cloud with minimal network latency.

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Unite.AI

MAY 29, 2023

Through the use of GenAI tools, powered by Nvidia Picasso and trained on responsibly sourced data, these teams can now rapidly generate virtual sets. Furthermore, they are utilizing Nvidia Isaac Sim to simulate and test robots and Nvidia Metropolis – a vision AI framework – for automated optical inspection.

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ODSC - Open Data Science

MAY 19, 2023

Researchers Create AI-powered Village With ChatGPT According to a new paper by researchers out of Sandford, they were able to create an entire Sim-like town using generative AI. With Dolly, they could start with a pre-trained LLM and fine-tune it on a data set of customer reviews. All of which interacted independently of each other.

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Google Research AI blog

DECEMBER 1, 2022

Code as Policies has shown that code-generating language models combined with pre-trained perception systems can produce language conditioned policies for zero shot robot manipulation. Because the robot is trained to follow open vocabulary language, we see it can react to a diverse set of verbal corrections (e.g.,

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The MLOps Blog

JANUARY 5, 2023

When we train models to do visual understanding of networks through visual understanding, we want more than that, we want to find features find connections in the images that are not that clear and it’s not possible to describe with text also. These triplet networks what is your go-to baseline triplet network training?

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Bugra Akyildiz

NOVEMBER 20, 2022

We created zpy to make synthetic data easy, by simplifying the simulation (sim) creation process and providing an easy way to generate synthetic data at scale. CML can help train and evaluate models — and then generate a visual report with results and metrics — automatically on every pull request.

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