Unite.AI

NOVEMBER 2, 2023

Here, “The Definitive Guide to Generative AI for Industry ” truly shines. The book starts by explaining what it takes to be a digital maverick and how enterprises can leverage digital solutions to transform how data is utilized. The solutions it presents bring us closer to a world of fully autonomous operations.

Generative AI 162

Generative AI Data Ingestion Large Language Models AI 162

Unite.AI

MARCH 3, 2025

Can you explain what neurosymbolic AI is and how it differs from traditional AI approaches? Our ultimate goal is to bring actionable transparency, where the AI systems can explain their reasoning in a way thats independently logically verifiable. Can you explain how it works and its significance in solving complex problems?

Automation 165

Automation Algorithm Explainability Large Language Models 165

AI News

DECEMBER 18, 2023

Zheng first explained how over a decade working in digital marketing and e-commerce sparked her interest more recently in data analytics and artificial intelligence as machine learning has become hugely popular. “There’s a lot of misconceptions, definitely.

Big Data 327

Big Data Neural Network Machine Learning Natural Language Processing 327

AWS Machine Learning Blog

FEBRUARY 19, 2025

More importantly, Automated Reasoning checks can explain why a statement is accurate using mathematically verifiable, deterministic formal logic. It requires precise, formal definition of rules and isnt suitable for subjective decisions that require human judgment. However, its important to understand its limitations.

Automation 77

Automation Explainability Auto-complete Generative AI 77

Towards AI

MARCH 17, 2024

Alongside this, there is a second boom in XAI or Explainable AI. Explainable AI is focused on helping us poor, computationally inefficient humans understand how AI “thinks.” First bringing together conflicting literature on what XAI is and some important definitions and distinctions.

Explainable AI 105

Explainable AI Explainability Neural Network AI 105

Unite.AI

JANUARY 30, 2025

The platform automatically analyzes metadata to locate and label structured data without moving or altering it, adding semantic meaning and aligning definitions to ensure clarity and transparency. Can you explain the core concept and what motivated you to tackle this specific challenge in AI and data analytics?

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Automation Metadata Explainability Data Scientist 147

Unite.AI

NOVEMBER 8, 2024

It’s not enough to simply identify unhappy customers — we help explain why and offer recommendations for immediate improvement, keeping customers satisfied in the moment. Can you explain how the AI algorithm processes these physiological signals and translates them into actionable insights for retailers?

Emotion AI 147

Emotion AI Algorithm Explainability Neural Network 147

AI News

MAY 3, 2024

. “Our AI engineers built a prompt evaluation pipeline that seamlessly considers cost, processing time, semantic similarity, and the likelihood of hallucinations,” Ros explained. It’s obviously an ambitious goal, but it’s important to our employees and it’s important to our clients,” explained Ros.

Big Data 324

Big Data Generative AI Explainability AI 324

Flipboard

APRIL 1, 2025

Unlike probabilistic approaches prevalent in machine learning, Automated Reasoning relies on formal mathematical logic to provide definitive guarantees about what can and cant be proven. Unlike probabilistic methods, it uses sound mathematical approaches to provide definitive guarantees about system behaviors within defined parameters.

Automation 161

Automation Generative AI AI AI 161

AI News

MAY 17, 2024

They built it in an afternoon,” Segura explains. Don’t think that’s a misnomer; the term is definitely ‘builder’. “I You don’t just wave it goodbye and never think about it again,” he explains. “At It took them a while to get to that point in maturity,” explains Segura. Segura likens it to offshoring processes.

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Automation Big Data Explainability Robotics 345

AI News

FEBRUARY 23, 2024

The announcement comes just days after Stability AI’s largest rival, OpenAI, unveiled Sora —a brand new AI model capable of generating nearly-realistic, high-definition videos from simple text prompts. Our commitment to ensuring generative AI is open, safe, and universally accessible remains steadfast,” explained Stability AI.

Big Data 331

Big Data OpenAI AI AI 331

Unite.AI

AUGUST 25, 2023

One of the most significant issues highlighted is how the definition of responsible AI is always shifting, as societal values often do not remain consistent over time. Can focusing on Explainable AI (XAI) ever address this? For someone who is being falsely accused, explainability has a whole different meaning and urgency.

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Explainability Explainable AI AI AI 246

Pickl AI

MARCH 6, 2025

Summary: This blog explains the differences between one-way ANOVA vs two-way ANOVA, their definitions, assumptions, and applications. Exploring Two-Way ANOVA: Definition and Purpose Two-way ANOVA extends one-way ANOVA by analysing the effects of two independent variables on a dependent variable simultaneously.

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Explainability Categorization Data Analysis 52

Unite.AI

FEBRUARY 10, 2025

They need reliable, predictable, and explainable results for complex multi-step workflows. We need a Plan Definition Language (PDL) that can be used to represent and reason about said courses of action and probabilities. And they need AI systems that mitigate, rather than exacerbate, the unpredictable nature of LLMs.

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LLM Software Engineer Explainability AI 173

Towards AI

OCTOBER 19, 2024

Quantization explained in plain English When BERT was released around 5 years ago, it triggered a wave of Large Language Models with ever increasing sizes. It is definitely not going to be as easy as rounding but it is surprisingly not that difficult either!

Explainability 105

Explainability LLM BERT Large Language Models 105

Flipboard

NOVEMBER 18, 2024

Aim to go back and forth explaining your reasoning and learning how you could approach your problem/idea differently. When I find myself stuck while getting started, I navigate right over to Claude and start explaining what I’m working on. We all tend to be a bit wordy in our first drafts (I'm definitely guilty of this!).

AI 159

AI AI Explainability ChatGPT 159

Towards AI

JANUARY 27, 2023

Deep Learning Explained: Perceptron The key concept behind every neural network. Mathematical definition We define the inputs ?, You now know the mathematical definition of a perceptron. As explained above, the bias is a scalar value that is added to the net input z before passing through the activation function.

Deep Learning 98

Deep Learning Explainability Neural Network Machine Learning 98

AWS Machine Learning Blog

DECEMBER 23, 2024

In this post, we explore why GraphRAG is more comprehensive and explainable than vector RAG alone, and how you can use this approach using AWS services and Lettria. At query time, user intent is turned into an efficient graph query based on domain definition to retrieve the relevant entities and relationship.

Generative AI 125

Generative AI Natural Language Processing Prompt Engineer Prompt Engineering 125

AI News

MARCH 7, 2024

Moving to text-to-image, Stability AI announced an early preview of Stable Diffusion 3 at the end of February, just days after OpenAI unveiled Sora, a brand new AI model capable of generating almost realistic, high definition videos from simple text prompts. While progress marches on, perfection remains difficult to attain.

Prompt Engineering 338

Prompt Engineering Prompt Engineer OpenAI Large Language Models 338

Flipboard

OCTOBER 13, 2023

In this first clip, he explains why he thinks generative AI is a major architectural shift in computing, and why it represents an opportunity for startups to get a leg up on incumbents. ” Anu does not think generative AI tools for writing software threaten the role of developers.

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Generative AI Explainability Software Engineer Large Language Models 176

Unite.AI

DECEMBER 1, 2023

SHAP's strength lies in its consistency and ability to provide a global perspective – it not only explains individual predictions but also gives insights into the model as a whole. This method requires fewer resources at test time and has been shown to effectively explain model predictions, even in LLMs with billions of parameters.

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LLM Machine Learning Explainability Algorithm 264

AI News

SEPTEMBER 17, 2024

In his book, Superintelligence, he talks about how AI can surpass our current definitions of intelligence and the possibilities that might ensue. He explains that the current age – the fourth industrial revolution – is building on the third: with far-reaching consequences.

Robotics 307

Robotics Artificial Intelligence Artificial Intelligence Big Data 307

IBM Journey to AI blog

JANUARY 25, 2024

The equation looks like this: A further study provided more calculations that refine the statistical definitions of a wise crowd, including ignorance of other members’ predictions and inclusion of those with maximally different (negatively correlated) predictions or judgements. How are you making your model explainable?

Algorithm 247

Algorithm Explainability AI AI 247

AI News

JULY 31, 2023

One definition of AI, however applicable only on a voluntary basis. Each sector can adopt a definition of AI and determine the riskiness of the AI systems covered. One horizontally applicable AI definition and methodology for the determination of high-risk (risk-based). The UK makes no regulatory changes regarding AI.

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AI AI Big Data Artificial Intelligence 246

Towards AI

FEBRUARY 14, 2024

Ah, more definitions U+1F92F. The regression part of the name is historical, I’ll explain it at the end. But let’s stick with ours, for now. A line function like ours is represented by the following equation: f(x) = a * x + bory = a * x + b Where: a is the slope and b is the intercept. So the function is linear.

Explainability 105

Explainability OpenAI ML AI Modeling 105

Flipboard

FEBRUARY 10, 2025

"I commission illustrations because I want to use a visual in an illustrator's unique style, but I also love working with artists on the ideas side, creating something new, fresh, current and bespoke," explains Claire.

AI 121

AI AI Large Language Models Explainability 121

O'Reilly Media

OCTOBER 22, 2024

I still clearly remember a developer, only two years my senior, explaining to me why I should be using ArrayList and not Vector. They will learn how to coach the AI to give them “better” code (for some definition of better) over time. Maybe, but we’re definitely not there yet.

Prompt Engineer 133

Prompt Engineer Prompt Engineering Generative AI Software Development 133

Flipboard

FEBRUARY 14, 2025

As De Kraker explained, xAI claimed that it asked the engineer to delete his post because he'd publicly referenced the forthcoming model despite Musk announcing it on the same platform more than a month prior.

AI Modeling 169

AI Modeling OpenAI AI AI 169

AWS Machine Learning Blog

FEBRUARY 21, 2025

The APIs standardized approach to tool definition and function calling provides consistent interaction patterns across different processing stages. When a document is uploaded through the Streamlit interface, Haiku analyzes the request and determines the sequence of tools needed by consulting the tool definitions in ToolConfig.

Categorization 84

Categorization IDP Generative AI Automation 84

Pickl AI

AUGUST 23, 2024

Summary: This blog post delves into the importance of explainability and interpretability in AI, covering definitions, challenges, techniques, tools, applications, best practices, and future trends. It highlights the significance of transparency and accountability in AI systems across various sectors.

Explainability 52

Explainability Deep Learning Machine Learning Neural Network 52

IBM Journey to AI blog

JUNE 26, 2023

One of the few pre-scripted questions I ask in most of the episodes is about the guest’s definition of “hybrid cloud.” Rob High explained the increasing importance of running applications in non-traditional places and on non-traditional devices, which we also often call “on the edge.”

DevOps 180

DevOps Explainability Automation AI 180

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. You define a denied topic by providing a natural language definition of the topic along with a few optional example phrases of the topic.

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Responsible AI Prompt Engineering Prompt Engineer AI 108

Unite.AI

JANUARY 15, 2025

Juggling school, a growing passion for technology, and starting a business was definitely challenging. Could you begin by explaining what PeaceTech is and why its important? What inspired you to take the leap into entrepreneurship, and how did you navigate the process of developing your first prototype?

Robotics 147

Robotics Computer Vision Automation Machine Learning 147

Marktechpost

APRIL 5, 2024

In their paper, the researchers aim to propose a theory that explains how transformers work, providing a definite perspective on the difference between traditional feedforward neural networks and transformers. Despite their widespread usage, the theoretical foundations of transformers have yet to be fully explored.

Neural Network 126

Neural Network Natural Language Processing Categorization Explainability 126

AWS Machine Learning Blog

JANUARY 31, 2025

By providing the FM with examples and other prompting techniques, we were able to significantly reduce the variance in the structure and content of the FM output, leading to explainable, predictable, and repeatable results.

Prompt Engineer 82

Prompt Engineer Prompt Engineering Data Scientist Large Language Models 82

AWS Machine Learning Blog

MARCH 27, 2025

In the following sections, we explain how to take an incremental and measured approach to improve Anthropics Claude 3.5 Designing the prompt Before starting any scaled use of generative AI, you should have the following in place: A clear definition of the problem you are trying to solve along with the end goal. client = boto3.client("bedrock-runtime",

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Categorization ETL Prompt Engineering Prompt Engineer 91

NVIDIA

JANUARY 29, 2025

With expertise on the intersection of autonomous systems and human-centered design, Covert explains the different stages of AI agents from basic conversational interfaces to fully autonomous systems. Time Stamps 5:34 The definition of digital humans and their current state in industries. 10:30 The evolution of AI agents.

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Neural Network Explainability AI AI 125