Marktechpost

MAY 15, 2024

Methods like Molecular Dynamics simulations, Quantitative Structure-Property Relationships (QSPR), and First-Principles calculations are based on scientific principles and complex mathematical models. Check out the Paper and Blog. This makes sure that the material space is fully covered. Also, don’t forget to follow us on Twitter.

Deep Learning 115

Deep Learning Machine Learning Generative AI ML 115

IBM Journey to AI blog

NOVEMBER 29, 2023

As all businesses strive to adopt a best-in-class approach for AI tools, let’s discuss best practices for how your company can leverage AI to enhance your real-time event processing use cases. Events as fuel for AI Models: Artificial intelligence models rely on big data to refine the effectiveness of their capabilities.

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Artificial Intelligence Artificial Intelligence Automation Machine Learning 234

IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. These insights can help drive decisions in business, and advance the design and testing of applications. Both computer scientists and business leaders have taken note of the potential of the data.

Data Science 148

Data Science DevOps Machine Learning Data Scientist 148

Marktechpost

MARCH 4, 2024

The proposed method, ViSNet, introduces a vector-scalar interactive graph neural network framework designed to enhance molecular geometry modeling. In conclusion, the model significantly improves the accuracy in predicting molecular properties and simulating molecular dynamics. Check out the Paper and Blog.

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Neural Network Algorithm ML AI 103

AWS Machine Learning Blog

OCTOBER 5, 2023

Artificial intelligence (AI) and machine learning (ML) have seen widespread adoption across enterprise and government organizations. Processing unstructured data has become easier with the advancements in natural language processing (NLP) and user-friendly AI/ML services like Amazon Textract , Amazon Transcribe , and Amazon Comprehend.

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NLP ML Natural Language Processing Artificial Intelligence 98

AWS Machine Learning Blog

MAY 9, 2024

The rapid advancements in artificial intelligence and machine learning (AI/ML) have made these technologies a transformative force across industries. An effective approach that addresses a wide range of observed issues is the establishment of an AI/ML center of excellence (CoE). What is an AI/ML CoE?

ML 100

ML Generative AI AI AI 100

AWS Machine Learning Blog

DECEMBER 19, 2023

Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. However, putting an ML model into production at scale is challenging and requires a set of best practices.

Machine Learning 107

Machine Learning ML Engineer DevOps ML 107

Towards AI

MAY 7, 2024

A collaboration between Nvidia and UPenn released DrEureka, a new open-source model that uses an LLM agent to write code for training robots in simulation and then write further code to transfer to real-world deployment. The model was trained on 8.1 The model scores 77.8 trillion tokens and has 21bn activated parameters.

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Robotics Chatbots OpenAI AI 79

Marktechpost

DECEMBER 19, 2023

Some researchers tried using machine learning to speed things up, but the models had issues. They treated two reactants as one thing, and if those reactants turned or rotated, the model got confused and thought it was a whole new reaction. To train this model, they used data from quantum chemistry for 9,000 different reactions.

Machine Learning 122

Machine Learning AI Researcher AI Research ML 122

IBM Journey to AI blog

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. However, if AGI development uses similar building blocks as narrow AI, some existing tools and technologies will likely be crucial for adoption.

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IBM Journey to AI blog

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. What is machine learning?

Data Science 151

Data Science Machine Learning Big Data Data Mining 151

IBM Journey to AI blog

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029. At Facebook Messenger, ML powers customer service chatbots.

Machine Learning 129

Machine Learning ML Algorithm Chatbots 129

Heartbeat

FEBRUARY 1, 2023

Machine learning has become an essential part of our lives because we interact with various applications of ML models, whether consciously or unconsciously. Machine Learning Operations (MLOps) are the aspects of ML that deal with the creation and advancement of these models. What is MLOps? What is MLOps?

DevOps 96

DevOps Machine Learning Data Scientist Software Engineer 96

Marktechpost

JULY 18, 2023

In recent years, Large Language Models (LLMs) have gained significant attention as a potential solution for detecting and classifying such misinformation. They primarily focused on four LLM models: Open AI’s Chat GPT-3.0 They primarily focused on four LLM models: Open AI’s Chat GPT-3.0 and Chat GPT-4.0,

Large Language Models 95

Large Language Models ChatGPT AI Tools AI 95

AWS Machine Learning Blog

NOVEMBER 16, 2023

This is a joint blog with AWS and Philips. Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. Philips is a health technology company focused on improving people’s lives through meaningful innovation.

Data Scientist 91

Data Scientist ML Data Science Automation 91

Marktechpost

JULY 1, 2023

A group of researchers from the University of Washington, Stanford, AI2, UCSB, and Google recently developed the OpenFlamingo project, which aims to build models similar to those DeepMind’s Flamingo team. OpenFlamingo models can handle any mixed text and image sequences and produce text as an output.

AI Tools 103

AI Tools AI Researcher AI Research ML 103

AWS Machine Learning Blog

JANUARY 5, 2024

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.

Data Science 113

Data Science Data Drift DevOps Auto-complete 113

Marktechpost

JULY 2, 2023

Diffusion models have been widely used with remarkable success in text-to-image generation in recent years, leading to significant improvements in image quality, inference performance, and the scope of our creative possibilities. Iterative denoising is modeled for image production in diffusion models.

Machine Learning 109

Machine Learning ML AI AI 109

AWS Machine Learning Blog

OCTOBER 30, 2023

Amazon Bedrock is a fully managed service provided by AWS that offers developers access to foundation models (FMs) and the tools to customize them for specific applications. It allows developers to build and scale generative AI applications using FMs through an API, without managing infrastructure.

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Generative AI ML Big Data Computer Vision 127

AWS Machine Learning Blog

JANUARY 26, 2024

Generative artificial intelligence (AI) applications built around large language models (LLMs) have demonstrated the potential to create and accelerate economic value for businesses. All the principles of the AWS Shared Responsibility Model are applicable to generative AI solutions.

Generative AI 125

Generative AI LLM ML AI 125

Marktechpost

JANUARY 23, 2024

Advanced prompting mechanisms, control flow, contact with external environments, many chained generation calls, and complex activities are expanding the utilization of Large Language Models (LLMs). Users can run an SGLang function through local models, OpenAI, Anthropic, and Gemini. Check out the Code and Blog.

LLM 101

LLM AI Researcher AI Research Auto-complete 101

Marktechpost

JULY 14, 2023

Research into computer architecture has a long history of producing simulators and tools for assessing and influencing computer system design. For instance, in the late 1990s, the SimpleScalar simulator was developed to let scientists test new microarchitecture concepts. Depending on the specifics of the model used (e.g.,

Machine Learning 98

Machine Learning Algorithm ML AI 98

AWS Machine Learning Blog

APRIL 8, 2024

Unlocking accurate and insightful answers from vast amounts of text is an exciting capability enabled by large language models (LLMs). When building LLM applications, it is often necessary to connect and query external data sources to provide relevant context to the model.

LLM 101

LLM Large Language Models Machine Learning Data Ingestion 101

AWS Machine Learning Blog

SEPTEMBER 20, 2023

In these scenarios, as you start to embrace generative AI, large language models (LLMs) and machine learning (ML) technologies as a core part of your business, you may be looking for options to take advantage of AWS AI and ML capabilities outside of AWS in a multicloud environment.

ML 102

ML Python Deep Learning Machine Learning 102

Towards AI

FEBRUARY 21, 2023

We test it on a practical problem in a modality of AI in which it was not trained, computer vision, and report the results. AI being in the limelight has spawned a deluge of thought pieces, articles, videos, blog posts, and podcasts. The average over ChatGPT metric suggestions, achieves on average 10.1% improvement in precision and 34.4%

ML Engineer 95

ML Engineer ML ChatGPT Computer Vision 95

Google Research AI blog

MARCH 30, 2023

Posted by Peter Mattson, Senior Staff Engineer, ML Performance, and Praveen Paritosh, Senior Research Scientist, Google Research, Brain Team Machine learning (ML) offers tremendous potential, from diagnosing cancer to engineering safe self-driving cars to amplifying human productivity. Each step can introduce issues and biases.

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AWS Machine Learning Blog

DECEMBER 13, 2023

Machine learning (ML) models do not operate in isolation. To deliver value, they must integrate into existing production systems and infrastructure, which necessitates considering the entire ML lifecycle during design and development. The SageMaker Model Registry centralizes model tracking, simplifying model deployment.

ML 103

ML Automation Metadata Software Development 103

John Snow Labs

OCTOBER 2, 2023

Imagine having the capability to seamlessly integrate state-of-the-art models from the Hugging Face Model Hub, harness diverse datasets effortlessly, rigorously test your models, compile comprehensive reports, and ultimately supercharge your NLP projects.

Responsible AI 52

Responsible AI Automation NLP Natural Language Processing 52

Marktechpost

JULY 19, 2023

A chatbot for taking notes, an editor for creating images from text, and a tool for summarising customer comments can all be made with a basic understanding of programming and a couple of hours. In the actual world, machine learning (ML) systems can embed issues like societal prejudices and safety worries.

Machine Learning 52

Machine Learning ML Python Metadata 52

AWS Machine Learning Blog

FEBRUARY 6, 2024

This document contains over 100 highly detailed technical reports created during the process of drug research and testing. By extracting key data from testing reports, the system uses Amazon SageMaker JumpStart and other AWS AI services to generate CTDs in the proper format. The following diagram illustrates the solution architecture.

Generative AI 105

Generative AI Large Language Models AI AI 105

AWS Machine Learning Blog

MARCH 6, 2024

In this post, we demonstrate how to efficiently fine-tune a state-of-the-art protein language model (pLM) to predict protein subcellular localization using Amazon SageMaker. This includes large language models (LLMs) pretrained on huge datasets, which can then be adapted for specific tasks, like text summarization or chatbots.

Neural Network 95

Neural Network Large Language Models Machine Learning ML 95

Heartbeat

SEPTEMBER 22, 2023

Introduction In the world of machine learning, where algorithms learn from data to make predictions, it’s important to get the best out of our models. But how do we ensure that our models perform at their best? Model Performance (Image by Author) 1. I write about Machine Learning on Medium || Github || Kaggle || Linkedin. ?

Machine Learning 64

Machine Learning ML Algorithm Automation 64

AWS Machine Learning Blog

SEPTEMBER 1, 2023

Nowadays, the majority of our customers is excited about large language models (LLMs) and thinking how generative AI could transform their business. However, bringing such solutions and models to the business-as-usual operations is not an easy task. Our approach applies to both open-source and proprietary models equally.

Generative AI 106

Generative AI Prompt Engineer Prompt Engineering AI 106

Heartbeat

JUNE 12, 2023

Source: Author Introduction Machine learning model monitoring tracks the performance and behavior of a machine learning model over time. It involves collecting and analyzing data on various aspects of the model’s performance, including its accuracy, precision, recall, and F1 score, as well as its bias , fairness , and stability.

Machine Learning 98

Machine Learning Data Drift Explainability Data Quality 98

AWS Machine Learning Blog

FEBRUARY 6, 2024

To support overarching pharmacovigilance activities, our pharmaceutical customers want to use the power of machine learning (ML) to automate the adverse event detection from various data sources, such as social media feeds, phone calls, emails, and handwritten notes, and trigger appropriate actions.

Large Language Models 100

Large Language Models BERT NLP Data Scientist 100

AWS Machine Learning Blog

MAY 23, 2023

This is a guest blog post co-written with Vik Pant and Kyle Bassett from PwC. With organizations increasingly investing in machine learning (ML), ML adoption has become an integral part of business transformation strategies. Many organizations start their journey into the world of ML with a model-centric viewpoint.

Machine Learning 74

Machine Learning Neural Network ML Data Scientist 74

AWS Machine Learning Blog

APRIL 29, 2024

In recent years, large language models (LLMs) have gained attention for their effectiveness, leading various industries to adapt general LLMs to their data for improved results, making efficient training and hardware availability crucial. This is a guest post by Mark McQuade, Malikeh Ehghaghi, and Shamane Siri from Arcee.

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Large Language Models NLP Machine Learning Artificial Intelligence 103