Unite.AI

MARCH 20, 2025

Algorithmic Bias in Decision-Making AI-powered recruitment tools can reinforce biases, impacting hiring decisions and creating legal risks. Similarly, criminal justice algorithms used in sentencing and parole decisions can diffuse racial disparities. Techniques like adversarial debiasing and re-weighting can reduce algorithmic bias.

Algorithm 162

Algorithm AI AI Explainability 162

IBM Journey to AI blog

OCTOBER 15, 2024

Fantasy football team owners are faced with complex decisions and an ocean of information. For the last 8 years, IBM has worked closely with ESPN to infuse its fantasy football experience with insights that help fantasy owners of all skill levels make more informed decisions. Why did it take so long? In a word: scale.

Explainability 257

Explainability Machine Learning Large Language Models Algorithm 257

NVIDIA

MARCH 17, 2025

Under the hood of every AI application are algorithms that churn through data in their own language, one based on a vocabulary of tokens. Tokens are tiny units of data that come from breaking down bigger chunks of information. How Are Tokens Used During AI Training?

Explainability 98

Explainability AI AI AI Modeling 98

IBM Journey to AI blog

APRIL 11, 2023

The new rules, which passed in December 2021 with enforcement , will require organizations that use algorithmic HR tools to conduct a yearly bias audit. Although some third-party vendor information may be proprietary, the evaluation team should still review these processes and establish safeguards for vendors.

AI Strategy 277

AI Strategy Algorithm Automation AI 277

Unite.AI

MARCH 3, 2025

Imandra is an AI-powered reasoning engine that uses neurosymbolic AI to automate the verification and optimization of complex algorithms, particularly in financial trading and software systems. Can you explain what neurosymbolic AI is and how it differs from traditional AI approaches? The field of AI has (very roughly!)

Automation 165

Automation Algorithm Explainability Large Language Models 165

Unite.AI

MAY 6, 2024

In a groundbreaking development , engineers at Northwestern University have created a new AI algorithm that promises to transform the field of smart robotics. Traditional algorithms, designed primarily for disembodied AI, are ill-suited for robotics applications.

Robotics 214

Robotics Algorithm Automation Explainability 214

Ehud Reiter

MARCH 2, 2025

Bayesian networks are causal graphs which contain probabilistic information about the relationship between nodes. However in practice they can be difficult to build and are not easy to explain, which limits their usefulness. Nikolay’s goal is to make BNs easier to build and explain, and hence more useful.

Explainability 129

Explainability Large Language Models Algorithm LLM 129

AI News

OCTOBER 8, 2024

At the University of Maryland (UMD), interdisciplinary teams tackle the complex interplay between normative reasoning, machine learning algorithms, and socio-technical systems. They aim to create AI systems that can learn rules from data while maintaining explainable decision-making processes grounded in legal and normative reasoning.

Artificial Intelligence 307

Artificial Intelligence Artificial Intelligence Explainability Big Data 307

Unite.AI

NOVEMBER 8, 2024

Inspired by a discovery in WiFi sensing, Alex and his team of developers and former CERN physicists introduced AI algorithms for emotional analysis, leading to Wayvee Analytics's founding in May 2023. The team engineered an algorithm that could detect breathing and micro-movements using just Wi-Fi signals, and we patented the technology.

Emotion AI 147

Emotion AI Algorithm Explainability Neural Network 147

Unite.AI

OCTOBER 29, 2024

By incorporating acoustic sensing capabilities, this new technology enables robots to gather detailed information about objects through physical interaction, similar to how humans instinctively use touch and sound to understand their surroundings. The development of SonicSense represents a significant leap forward in bridging this gap.

Robotics 162

Robotics Explainability Algorithm Automation 162

Towards AI

FEBRUARY 3, 2024

(Left) Photo by Pawel Czerwinski on Unsplash U+007C (Right) Unsplash Image adjusted by the showcased algorithm Introduction It’s been a while since I created this package ‘easy-explain’ and published on Pypi. A few weeks ago, I needed an explainability algorithm for a YoloV8 model. The truth is, I couldn’t find anything.

Explainability 126

Explainability Explainable AI Neural Network Algorithm 126

Unite.AI

DECEMBER 27, 2024

Without data, even the most complex algorithms are useless. AI systems need vast information to learn patterns, predict, and adapt to new situations. Many platforms collect personal information without clearly explaining how it will be used. The Role of Data in AI Development Data is the foundation of AI.

AI 173

AI AI Natural Language Processing AI Modeling 173

IBM Journey to AI blog

AUGUST 9, 2024

Predictive AI blends statistical analysis with machine learning algorithms to find data patterns and forecast future outcomes. In short, predictive AI helps enterprises make informed decisions regarding the next step to take for their business. What is predictive AI? What’s the difference between generative AI and predictive AI?

Generative AI 301

Generative AI Explainability AI AI 301

Unite.AI

MARCH 14, 2024

For many institutional investors, the answer is likely to be no – that the potential benefits of AI just aren’t worth the risk associated with a process they aren’t able to understand, much less explain to their boards and clients. But there is a way out of this dilemma.

Black Box AI 299

Black Box AI Explainability Algorithm AI 299

Unite.AI

SEPTEMBER 12, 2024

In a significant leap forward, researchers at the University of Southern California (USC) have developed a new artificial intelligence algorithm that promises to revolutionize how we decode brain activity. DPAD: A New Approach to Neural Decoding The DPAD algorithm represents a paradigm shift in how we approach neural decoding.

Algorithm 162

Algorithm Neural Network Artificial Intelligence Artificial Intelligence 162

Unite.AI

DECEMBER 27, 2024

No matter how advanced an algorithm is, noisy, biased, or insufficient data can bottleneck its potential. While massive, overly influential datasets can enhance model performance , they often include redundant or noisy information that dilutes effectiveness. Another promising development is the rise of explainable data pipelines.

Data Quality 130

Data Quality Data Drift Explainability Big Data 130

Unite.AI

NOVEMBER 22, 2024

It helps explain how AI models, especially LLMs, process information and make decisions. This makes it easier to track how the AI processes and prioritizes information. Mapping Information Flow Gemma Scope can help track the flow of data through a model by analyzing activation signals at each layer.

Large Language Models 113

Large Language Models Neural Network AI AI 113

Unite.AI

DECEMBER 12, 2024

While current AI systems excel at processing information and generating responses, the next generation of AI needs to do something far more challenging: take meaningful action in both digital and physical spaces. Or between an AI that can explain code and one that can write and debug it in real-time.

Natural Language Processing 162

Natural Language Processing Computer Vision AI AI 162

Unite.AI

NOVEMBER 21, 2024

Unlike batch-processing systems, it does not wait for intervals to process information. Why Drasi Matters for Real-Time Data As data generation continues to grow rapidly, companies are under increasing pressure to process and respond to information as it becomes available. That is where Drasi by Microsoft comes in.

Machine Learning 147

Machine Learning Data Ingestion Automation Artificial Intelligence 147

AI News

NOVEMBER 21, 2023

So that’s a key area of focus,” explains O’Sullivan. Safeguarding data privacy is also paramount, with stringent measures needed to prevent the misuse of sensitive customer information. Concerns about hallucinations – where AI systems generate inaccurate or misleading information – must be addressed meticulously.

Big Data 328

Big Data Data Quality Generative AI Explainability 328

Unite.AI

JUNE 26, 2023

Theoretical frameworks such as Integrated Information Theory (IIT), Global Workspace Theory (GWT), and Artificial General Intelligence (AGI) provide a frame of reference for how AI consciousness can be achieved. AI models are becoming more complex, with billions of parameters capable of processing and integrating large volumes of information.

AI 348

AI AI Neural Network Natural Language Processing 348

Unite.AI

JUNE 26, 2023

Similarly, what if a drug diagnosis algorithm recommends the wrong medication for a patient and they suffer a negative side effect? Most AI today use “black box” logic, meaning no one can see how the algorithm makes decisions. Explainable AI — also known as white box AI — may solve transparency and data bias concerns.

Black Box AI 297

Black Box AI Explainable AI Explainability AI 297

Unite.AI

MARCH 6, 2025

It analyzes over 250 data points per property using proprietary algorithms to forecast which homes are most likely to list within the next 12 months. The platform delivers daily leads and contact information for predicted sellers, along with automated outreach tools. updated multiple times per week.

AI 182

AI AI Automation Algorithm 182

Unite.AI

DECEMBER 13, 2023

Importance of Staying Updated on Trends Staying updated on AI trends is crucial because it keeps you informed about the latest advancements, ensuring you remain at the forefront of technological innovation. Regulatory Compliance and Explainability Regulatory bodies are focusing on transparency and accountability.

Explainability 290

Explainability AI AI Responsible AI 290

Marktechpost

JANUARY 14, 2025

Explaining Machine Learning Machine Learning is a branch of Artificial Intelligence ( AI ) that allows systems to learn and improve from data without being explicitly programmed. IBM describes Machine Learning as “training algorithms to process and analyze data to make predictions or decisions with minimal human intervention.”

Machine Learning 79

Machine Learning ML Algorithm Artificial Intelligence 79

AI News

APRIL 29, 2024

However, just because OpenAI is cozying up to publishers doesn’t mean it’s not still scraping information from the web without permission. OpenAI understands the importance of transparency, attribution, and compensation – all essential for us,” explained Ridding.

OpenAI 324

OpenAI Big Data ChatGPT Large Language Models 324

Marktechpost

AUGUST 7, 2024

The Role of Explainable AI in In Vitro Diagnostics Under European Regulations: AI is increasingly critical in healthcare, especially in vitro diagnostics (IVD). The European IVDR recognizes software, including AI and ML algorithms, as part of IVDs. This includes considering patient population, disease conditions, and scanning quality.

Explainable AI 107

Explainable AI Explainability Neural Network Algorithm 107

PyImageSearch

OCTOBER 14, 2024

This blog post is the 1st of a 3-part series on 3D Reconstruction: Photogrammetry Explained: From Multi-View Stereo to Structure from Motion (this blog post) 3D Reconstruction: Have NeRFs Removed the Need for Photogrammetry? 3D Gaussian Splatting: The End Game of 3D Reconstruction? To learn about 3D Reconstruction, just keep reading.

Explainability 114

Explainability Computer Vision Deep Learning Algorithm 114

NVIDIA

MARCH 26, 2025

Kaitlyn Albertoli, CEO and cofounder of Buzz Solutions joined the AI Podcast to explain how the companys vision AI technology helps utilities spot potential problems faster. 20:00: Buzz Solutions innovative use of synthetic data to train algorithms for rare events. So, too, are concerns about advanced technologys environmental impact.

Explainability 75

Explainability Actionable Intelligence Software Development AI 75

AWS Machine Learning Blog

NOVEMBER 26, 2024

In this post, we discuss how to use LLMs from Amazon Bedrock to not only extract text, but also understand information available in images. Solution overview In this post, we demonstrate how to use models on Amazon Bedrock to retrieve information from images, tables, and scanned documents. 90B Vision model.

LLM 103

LLM Convolutional Neural Networks Metadata Explainability 103

AWS Machine Learning Blog

NOVEMBER 15, 2024

For now, we consider eight key dimensions of responsible AI: Fairness, explainability, privacy and security, safety, controllability, veracity and robustness, governance, and transparency. Such words can include offensive terms or undesirable outputs, like product or competitor information.

Responsible AI 110

Responsible AI Prompt Engineering Prompt Engineer AI 110

Unite.AI

DECEMBER 1, 2023

Machine learning , a subset of AI, involves three components: algorithms, training data, and the resulting model. An algorithm, essentially a set of procedures, learns to identify patterns from a large set of examples (training data). The culmination of this training is a machine-learning model.

LLM 264

LLM Machine Learning Explainability Algorithm 264

PyImageSearch

OCTOBER 28, 2024

Home Table of Contents NeRFs Explained: Goodbye Photogrammetry? Block #A: We Begin with a 5D Input Block #B: The Neural Network and Its Output Block #C: Volumetric Rendering The NeRF Problem and Evolutions Summary and Next Steps Next Steps Citation Information NeRFs Explained: Goodbye Photogrammetry? How Do NeRFs Work?

Explainability 99

Explainability Neural Network Computer Vision Deep Learning 99

Unite.AI

MAY 27, 2024

AI, on the other hand, leverages machine learning (ML) algorithms that can analyze vast amounts of data, including transaction history, location, and device information, to identify anomalies and suspicious activity in real-time. One of the key challenges in AI is explainability.

Machine Learning 223

Machine Learning Explainability Algorithm AI 223

IBM Journey to AI blog

JANUARY 25, 2024

These issues require more than a technical, algorithmic or AI-based solution. Consider, for example, who benefits most from content-recommendation algorithms and search engine algorithms. Algorithms and models require targets or proxies for Bayes error: the minimum error that a model must improve upon.

Algorithm 247

Algorithm Explainability AI AI 247

Unite.AI

JULY 19, 2024

That's an AI hallucination, where the AI fabricates incorrect information. The consequences of relying on inaccurate information can be severe for these industries. These tools help identify when AI makes up information or gives incorrect answers, even if they sound believable. This reduces the likelihood of hallucinations.

LLM 279

LLM AI AI Data Quality 279

Flipboard

FEBRUARY 27, 2025

Then again, though, Recipes Time isn't designed to help provide useful information from real experts explaining how to install new shelves or cook a healthy dinner, for that matter. The AI-generated articles, he explains, are then published to a website featuring another fake author.

AI 182

AI AI Explainability ChatGPT 182