Ocean Protocol

JANUARY 17, 2024

It would run according to default settings: what price feeds to use for AI model inputs, how much training data, etc. epochs to train model on autoregressive_n : 10 # no. It grabs historical data, builds models, predicts, does simulated trades, then repeats, all on historical data. It logs and plots progress in real time.

Data Pipeline 52

Data Pipeline AI AI Analytics 52

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.

Algorithm 139

Algorithm System Architecture Deep Learning Deep Learning 139

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?

Machine Learning 76

Machine Learning Machine Learning AWS ML 76

Ocean Protocol

FEBRUARY 27, 2024

Upgrades to Simulator The prediction/trading simulator pdr sim got upgraded. Sim prediction bots are now two-sided , behaving just like in the main predictoor bots. Sim trading bots are now confidence-based. Or, run for yourself with pdr sim my_ppss.yaml. The updated “pdr sim” realtime plot, having many sub-plots.

Data Pipeline 59

Data Pipeline AI AI Analytics 59

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.

ML 90

ML ML AWS AI 90

Dataconomy

JUNE 9, 2023

Keep reading… Image courtesy: Photoleap AI photo editor AI 101 You can still get on the AI train! The only limit is your imagination! We have created a detailed AI glossary for the most commonly used artificial intelligence terms and explain the basics of artificial intelligence as well as the risks and benefits of AI.

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AI AI Artificial Intelligence Artificial Intelligence 171

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.

Algorithm 89

Algorithm 89

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.

AI 67

AI AI Deep Learning Deep Learning 67

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?

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

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).

Machine Learning 98

Machine Learning Machine Learning 98

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?

Machine Learning 52

Machine Learning Machine Learning Database ML 52

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.

Data Science 52

Data Science AI AI Artificial Intelligence 52

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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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.,

ML 52

ML ML Supervised Learning Machine Learning 52

Explosion

FEBRUARY 28, 2017

sim, bp_sim = similarity_metric(vec1, vec2) def backward(d_sim, optimize): d_vec1, d_vec2 = bp_sim(d_sim, optimize) d_text1 = bp_vec1(d_vec1, optimize) d_text2 = bp_vec2(d_vec2, optimize) return d_text1, d_text2 return sim, backward return forward I recommend Chen’s discussion of the Siamese network. No dropout is applied.

Algorithm 40

Algorithm Clustering 40

Mlearning.ai

JUNE 27, 2023

Example: If we have k=3, then we get C1, C2, C3 as clusters and пow, if we want k=7, then we need to re-train to get the following clusters.There is no way get the clusters organically (or) easily, we need to redo to get the desired output. Sim(C1,C2) = max [Sim(Pi,Pj)] Such that Pi belongs to C1 & Pj belongs to C2. (or)

Clustering 52

Clustering Algorithm Computer Science Computer Science 52

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.

Algorithm 98

Algorithm Artificial Intelligence Artificial Intelligence Supervised Learning 98