Ars Technica

MARCH 17, 2025

The result of all those variations in technique is a great deal of variability in quality and taste. For instance, in 2020, Christopher Hendon's lab at the University of Oregon helped devise a mathematical model for brewing the perfect cup of espresso over and over while minimizing waste. Naturally, scientists find this fascinating.

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Ars Technica

FEBRUARY 13, 2025

On Wednesday, OpenAI CEO Sam Altman announced a roadmap for how the company plans to release GPT-5, the long-awaited followup to 2023's GPT-4 AI language model that made huge waves in both tech and policy circles around the world. previously known as "Orion" internally) in a matter of " weeks " as OpenAI's last non-simulated reasoning model.

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Machine Learning Mastery

JANUARY 9, 2025

Large language models (LLMs) are useful for many applications, including question answering, translation, summarization, and much more, with recent advancements in the area having increased their potential.

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Fast Company Tech

MARCH 31, 2025

A New York-based AI startup called Hebbia says it’s developed techniques that let AI answer questions about massive amounts of data without merely regurgitating what it’s read or, worse, making up information. Hebbia, says Sivulka, has approached the problem with a technique the company calls iterative source decomposition.

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Machine Learning Mastery

AUGUST 30, 2024

Predictive modeling in finance uses historical data to forecast future trends and outcomes. R, a powerful statistical programming language, provides a robust set of tools and libraries for financial analysis and modeling.

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TechCrunch

NOVEMBER 16, 2021

Machine learning is exploding, and so are the number of models out there for developers to choose from. While Google can help, it’s not really designed as a model search engine. The brothers grew up in New Delhi in an area that was originally for refugees from when the British split India and Pakistan in the late 1940s.

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Machine Learning Mastery

JANUARY 6, 2025

With large language model (LLM) products such as ChatGPT and Gemini taking over the world, we need to adjust our skills to follow the trend. One skill we need in the modern era is prompt engineering. Prompt engineering is the strategy of designing effective prompts that optimize the performance and output of LLMs. By structuring […]

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Machine Learning Mastery

MAY 5, 2024

The image diffusion model, in its simplest form, generates an image from the prompt. The prompt can be a text prompt or an image as long as a suitable encoder is available to convert it into a tensor that the model can use as a condition to guide the generation process.

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Machine Learning Mastery

SEPTEMBER 9, 2024

This post will demonstrate the usage of Lasso, Ridge, and ElasticNet models using the Ames housing dataset. These models are particularly valuable when dealing with data that may suffer from multicollinearity.

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Machine Learning Mastery

MARCH 7, 2023

A popular demonstration of the capability of deep learning techniques is object recognition in image data. The “hello world” of object recognition for machine learning and deep learning is the MNIST dataset for handwritten digit recognition.

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Google Research AI blog

JANUARY 18, 2023

I will begin with a discussion of language, computer vision, multi-modal models, and generative machine learning models. Language Models The progress on larger and more powerful language models has been one of the most exciting areas of machine learning (ML) research over the last decade. Let’s get started!

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Machine Learning Mastery

OCTOBER 12, 2024

Feature engineering and model training form the core of transforming raw data into predictive power, bridging initial exploration and final insights. This guide explores techniques for identifying important variables, creating new features, and selecting appropriate algorithms.

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Google Research AI blog

MAY 15, 2023

In general, models’ success at in-context learning is enabled by: Their use of semantic prior knowledge from pre-training to predict labels while following the format of in-context examples (e.g., Flipped-label ICL uses flipped labels, forcing the model to override semantic priors in order to follow the in-context examples.

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TechCrunch

APRIL 19, 2023

Stability AI , the startup behind the generative AI art tool Stable Diffusion , today open-sourced a suite of text-generating AI models intended to go head to head with systems like OpenAI’s GPT-4. make up) facts. “This is expected to be improved with scale, better data, community feedback and optimization.”

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Language Model Open Source Technique 100

NVIDIA AI Blog

JANUARY 31, 2025

The recently released DeepSeek-R1 model family has brought a new wave of excitement to the AI community, allowing enthusiasts and developers to run state-of-the-art reasoning models with problem-solving, math and code capabilities, all from the privacy of local PCs.

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TechSpot

JUNE 26, 2024

Looking to change that, the researchers trimmed out an intensive technique called matrix multiplication. This technique assigns words to numbers, stores them in matrices, and multiples them together to create. AI up to this point has largely been a race to be first, with little consideration for metrics like efficiency.

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Technique Model Metrics Time 119

Google Research AI blog

MAY 19, 2023

Posted by Natalia Ponomareva and Alex Kurakin, Staff Software Engineers, Google Research Large machine learning (ML) models are ubiquitous in modern applications: from spam filters to recommender systems and virtual assistants. These models achieve remarkable performance partially due to the abundance of available training data.

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DataRobot

APRIL 29, 2022

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. When business decisions are made based on bad models, the consequences can be severe. As machine learning advances globally, we can only expect the focus on model risk to continue to increase.

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Model Government Policy Case Study 111

Google Research AI blog

NOVEMBER 10, 2022

Posted by Jason Wei and Yi Tay, Research Scientists, Google Research, Brain Team The field of natural language processing (NLP) has been revolutionized by language models trained on large amounts of text data. Scaling up the size of language models often leads to improved performance and sample efficiency on a range of downstream NLP tasks.

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TechCrunch

JULY 13, 2022

Companies face several hurdles in creating text-, audio- and image-analyzing AI models for deployment across their apps and services. Cost is an outsize one — training a single model on commercial hardware can cost tens of thousands of dollars, if not more. Geifman proposes neural architecture search (NAS) as a solution.

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TechCrunch

FEBRUARY 27, 2023

Anthropic , a buzzy AI startup co-founded by ex-OpenAI employees, has begun offering partners access to its AI text-generating models. Quora’s experimental chatbot app for iOS and Android, Poe , uses Anthropic models, but it’s not currently monetized. Robin AI is one of the first commercial ventures to use Anthropic models.

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Generation Model Pledge Google 102

Towards Data Science

FEBRUARY 24, 2023

Build clean nested data models for use in data engineering pipelines Photo by Didssph on Unsplash Introduction Pydantic is an incredibly powerful library for data modeling and validation that should become a standard part of your data pipelines. We can see that 4 other models underneath it support our top-level model.

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InfoWorld

DECEMBER 25, 2023

Here the rapid pace of innovation in model quantization, a technique that results in faster computation by improving portability and reducing model size, is playing a pivotal role.

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Model Technique Analytics Roles 81

Towards Data Science

FEBRUARY 9, 2023

An experiment on BigQuery If you are processing a couple of MB or GB with your dbt model, this is not a post for you; you are doing just fine! In this post, I will go over a technique for enabling a cheap data injestion and cheap data consumption for “big data”. GB and the daily load scans 536.6

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Fast Company Tech

MARCH 8, 2025

We use a machine learning technique called conformal prediction. But the higher the confidence level, the more polymer predictions given by the model in the output. Our recent work addresses this issue by creating a tool with an uncertainty quantification for microplastic identification.

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Recode by Vox

MARCH 13, 2025

The newest reasoning models from top AI companies are already essentially human-level, if not superhuman, at many programming tasks , which in turn has already led new tech startups to hire fewer workers. Fast AI progress, slow robotics progress If youve heard of OpenAI, youve heard of its language models: GPTs 1, 2, 3, 3.5,

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Laptop Classes Job Model 91

TechCrunch

JULY 19, 2022

Even shielded behind an API, hackers can attempt to reverse-engineer the models underpinning these services or use “adversarial” data to tamper with them. In fact, at HiddenLayer, we believe we’re not far off from seeing machine learning models ransomed back to their organizations.”

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Machine Learning Mastery

JUNE 21, 2024

If you are a machine learning student, researcher, or practitioner, it is crucial for your career growth to have a deep understanding of how each algorithm works and the various techniques to enhance model performance.

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InfoWorld

FEBRUARY 15, 2024

Whether it’s large-scale, public large language models (LLM) like GPT or small-scale, private models trained on company content, developers need to find ways of including those models in their code. We can build on some of the MLOps concepts used to manage the underlying models, merging them with familiar devops techniques.

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TechSpot

MARCH 30, 2025

Circuit tracing is a relatively new technique that lets researchers track how an AI model builds its answers step by step like following the wiring in a brain. It works by chaining together different components of a model. Anthropic used it to spy on Claude's inner workings. This revealed. Read Entire Article

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TechCrunch

JANUARY 25, 2023

Tanmay Chopra Contributor Share on Twitter Tanmay Chopra works in machine learning at AI search startup Neeva , where he wrangles language models large and small. Last summer could only be described as an “AI summer,” especially with large language models making an explosive entrance. Let’s start with buying.

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Nonprofit Tech for Good

OCTOBER 22, 2020

What happens online must follow the same offline prospecting to identification to qualification to cultivation to solicitation to stewardship model. The techniques are the same; it is just the medium that is different.

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Social Media Donor Social Media 354

TechSpot

MARCH 25, 2022

Nvidia's AI research arm has been working on inverse rendering and developed a Neural Radiance Field it calls Instant NeRF because it can render the 3D scene up to 1,000-times faster than other NeRF techniques. The AI model only needs a few seconds to train on a few dozen stills.

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Machine Learning Mastery

SEPTEMBER 12, 2024

In our previous exploration of penalized regression models such as Lasso, Ridge, and ElasticNet, we demonstrated how effectively these models manage multicollinearity, allowing us to utilize a broader array of features to enhance model performance.

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Machine Learning Mastery

SEPTEMBER 17, 2024

Our discussion so far has been anchored around the family of linear models. Each approach, from simple linear regression to penalized techniques like Lasso and Ridge, has offered invaluable insights into predicting continuous outcomes based on linear relationships.

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TechSpot

MARCH 18, 2024

University researchers have developed a way to "jailbreak" large language models like Chat-GPT using old-school ASCII art. The technique, aptly named "ArtPrompt," involves crafting an ASCII art "mask" for a word and then cleverly using the mask to coax the chatbot into providing a response it shouldn't. Read Entire Article

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The AI Alignment Forum

MARCH 13, 2025

Published on March 13, 2025 7:18 PM GMT We study alignment audits systematic investigations into whether an AI is pursuing hidden objectivesby training a model with a hidden misaligned objective and asking teams of blinded researchers to investigate it. As a testbed, we train a language model with a hidden objective.

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