Unite.AI

JANUARY 12, 2024

These innovations signal a shifting priority towards multimodal, versatile generative models. Competitions also continue heating up between companies like Google, Meta, Anthropic and Cohere vying to push boundaries in responsible AI development. Enhancing user trust via explainable AI also remains vital.

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Marktechpost

JULY 6, 2023

It is crucial to distinguish between IAI and XAI models because of their increasing popularity in the ML field in order to assist organizations in selecting the best strategy for their use case. In other words, it is safe to say that an IAI model provides its own explanation. Situations of this nature can be interpreted.

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Marktechpost

AUGUST 13, 2024

However, the challenge lies in integrating and explaining multimodal data from various sources, such as sensors and images. AI models are often sensitive to small changes, necessitating a focus on trustworthy AI that emphasizes explainability and robustness.

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Robotics Explainability Explainable AI Categorization 105

Towards AI

APRIL 2, 2024

What happened this week in AI by Louie The ongoing race between open and closed-source AI has been a key theme of debate for some time, as has the increasing concentration of AI research and investment into transformer-based models such as LLMs. X’s Grok Chatbot Will Soon Get an Upgraded Model, Grok-1.5

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Marktechpost

SEPTEMBER 11, 2024

Explainable AI (XAI) has emerged as a critical field, focusing on providing interpretable insights into machine learning model decisions. Self-explaining models, utilizing techniques such as backpropagation-based, model distillation, and prototype-based approaches, aim to elucidate decision-making processes.

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Explainability Explainable AI Machine Learning AI 56

Marktechpost

JULY 19, 2023

Researchers have also shown that explainable AI, which is when an AI model explains at each step why it took a certain decision instead of just providing predictions, does not reduce this problem of AI overreliance. All Credit For This Research Goes To the Researchers on This Project.

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Artificial Intelligence Artificial Intelligence Explainability Explainable AI 52

ODSC - Open Data Science

FEBRUARY 18, 2025

This is not science fiction, as these are the promises of PhD-level AI agentshighly autonomous systems capable of complex reasoning, problem-solving, and adaptive learning. Unlike traditional AI models, these agents go beyond pattern recognition to independently analyze, reason, and generate insights in specialized fields.

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ODSC - Open Data Science

FEBRUARY 25, 2025

Generative AI TrackBuild the Future with GenAI Generative AI has captured the worlds attention with tools like ChatGPT, DALL-E, and Stable Diffusion revolutionizing how we create content and automate tasks. Whats Next in AI TrackExplore the Cutting-Edge Stay ahead of the curve with insights into the future of AI.

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Data Scientist Machine Learning Large Language Models ML Engineer 52

AI Impacts

DECEMBER 22, 2022

I don’t have a strong view on whether anything in the space of ‘try to slow down some AI research’ should be done. Formulate specific precautions for AI researchers and labs to take in different well-defined future situations, Asilomar Conference style. And lately , to a bunch of other people.)

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The MLOps Blog

FEBRUARY 27, 2025

For example, a large language model is intentionally biased toward generating grammatically correct sentences. The challenge for AI researchers and engineers lies in separating desirable biases from harmful algorithmic biases that perpetuate social biases or inequity. The real challenge lies in how the service is used.

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LLM Large Language Models Explainability Machine Learning 64

Snorkel AI

MARCH 19, 2024

In an ideal world, every company could easily and securely leverage its own proprietary data sets and assets in the cloud to train its own industry/sector/category-specific AI models. There are multiple approaches to responsibly provide a model with access to proprietary data, but pointing a model at raw data isn’t enough.

Data Scientist 52

Data Scientist LLM Chatbots AI 52

Snorkel AI

MARCH 19, 2024

In an ideal world, every company could easily and securely leverage its own proprietary data sets and assets in the cloud to train its own industry/sector/category-specific AI models. There are multiple approaches to responsibly provide a model with access to proprietary data, but pointing a model at raw data isn’t enough.

Data Scientist 52

Data Scientist Chatbots AI AI 52

Marktechpost

JULY 11, 2023

Stacking is an approach that lets AI models use other models as tools or mediums to accomplish a task. Don’t forget to join our 19k+ ML SubReddit , Discord Channel , and Email Newsletter , where we share the latest AI research news, cool AI projects, and more.

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Auto-complete Generative AI Large Language Models OpenAI 40

IBM Journey to AI blog

SEPTEMBER 3, 2024

And while organizations are taking advantage of technological advancements such as generative AI , only 24% of gen AI initiatives are secured. This lack of security threatens to expose data and AI models to breaches, the global average cost of which is a whopping USD 4.88 Choose energy-efficient AI models or frameworks.

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The MLOps Blog

AUGUST 11, 2023

OpenAI, on the other hand, has been at the forefront of advancements in generative AI models, such as GPT-3, which heavily rely on embeddings. The concept of Explainable AI revolves around developing models that offer inference results and a form of explanation detailing the process behind the prediction.

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