OpenAI has announced a significant expansion of its ChatGPT platform, introducing a new generation of interactive applications that seamlessly integrate with the chatbot. This development aims to transform ChatGPT into a comprehensive conversational assistant capable of performing tasks across various domains. Introduction of Apps in ChatGPT OpenAI has launched a suite of applications within ChatGPT, […] The post OpenAI Unveils ChatGPT App Store and Developer SDK appeared first on AIT365.| AIT365
I made the audio version of this post available for free on my Patreon! You can subscribe to get lots of other audio recordings of blog posts, too. Photo Credit: Tyler Pasciak LaRiviere for the Chi…| Chelsea Troy
AI is a field that creates intelligent systems, and Machine Learning is the dominant approach for achieving that intelligence by learning patterns from data.| Data School
When analyzing time series data, your main objective is to consider the period during which the data is collected and how your variable of interest changes over time. There are various libraries for time series forecasting in Python, and Darts is one...| freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
Gesture and sign recognition is a growing field in computer vision, powering accessibility tools and natural user interfaces. Most beginner projects rely on hand landmarks or small CNNs, but these often miss the bigger picture because gestures are no...| freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
When I started using LLMs for work and personal use, I picked up on some technical terms, such as "machine learning" and "deep learning," which are the main technologies behind these LLMs. I've always been interested in learning about the differences...| freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
Salesforce AI Research released CoDA-1.7B, a diffusion-based language model for code that generates by denoising whole sequences with bidirectional context, updating multiple tokens in parallel rather than left-to-right next-token prediction. The research team published both Base and Instruct checkpoints and an end-to-end training/evaluation/serving stack. Understanding the architecture and training CoDA adapts a 1.7B-parameter backbone to […] The post Salesforce AI Research Releases CoDA-1...| MarkTechPost
We will build a Regression Language Model (RLM), a model that predicts continuous numerical values directly from text sequences in this coding implementation. Instead of classifying or generating text, we focus on training a transformer-based architecture that learns quantitative relationships hidden within natural language descriptions. We start by generating synthetic text-to-number data, tokenizing it efficiently, […] The post A Coding Implementation to Build a Transformer-Based Regressi...| MarkTechPost
Researchers from Cornell and Google introduce a unified Regression Language Model (RLM) that predicts numeric outcomes directly from code strings—covering GPU kernel latency, program memory usage, and even neural network accuracy and latency—without hand-engineered features. A 300M-parameter encoder–decoder initialized from T5-Gemma achieves strong rank correlations across heterogeneous tasks and languages, using a single text-to-number decoder […] The post Can a Small Language Model ...| MarkTechPost
You probably think twice before downloading a random app or opening an unfamiliar email attachment. But how often do you stop to consider what happens when your team downloads and loads a machine learning model? A recent study shows why you should. Researchers from Politecnico di Milano found that loading a shared model can be just as risky as running untrusted code. In their tests, they uncovered six previously unknown flaws in popular machine learning … More → The post When loading a mo...| Help Net Security
Artificial Intelligence, Machine Learning, Computer Science| Lei Mao's Log Book
The past posts on optimization scaling laws [1, 2] focused on problems that do not become significantly harder as the problem size increases. We showed that for some problems, as the dimension \(d\) goes to infinity, the optimality gap converges at a sublinear rate \(\Theta(k^{-p})\) for some power \(p\) depending on the problem, but independent of \(d\). But not all problems have this nice limiting behavior, and some become harder as the problem size increases.| Machine Learning Research Blog
Assumed audience: Mid career technical researchers considering moving into AI Safety research, career advisors in the EA/AI Safety space, AI Safety employers and grantmakers Nonetl;dr AI career advice orgs, prominently 80,000 Hours, encourage career moves into AI risk roles, including mid‑career pivots into roles in AI safety research labs. Without side information, that advice is not credible for mid‑career readers, because it does not have a calibration mechanism. Advice organizations i...| The Dan MacKinlay stable of variably-well-consider’d enterprises
Figure 1 Agent foundations is the branch of AI alignment that tries to answer: if we were to build a superintelligent system from scratch, what clean, mathematical objective could we give it so that it robustly does what we want, even if we cannot understand the system ourselves? Unlike interpretability (which inspects black-box models) or preference learning (which tries to extract human values), agent foundations is about first principles: designing an agent that’s “aligned by construc...| The Dan MacKinlay stable of variably-well-consider’d enterprises
Figure 1 I’m working on some proposals in AI safety at the moment, including this one. I submitted this particular one to the UK AISI Alignment Project. It was not funded. Note that this post is different than many on this blog. It’s highly speculative and yet not that measured; that’s because it’s a pitch, not an analysis. It doesn’t contain a credible amount of detail (there were only two text fields with a 500 word limit to explain the whole thing) I present it here for comment ...| The Dan MacKinlay stable of variably-well-consider’d enterprises
Wherein a failed application is set forth, and two research pathways are outlined: a Bias‑Robust Oversight programme at UTS’s Human Technology Institute, and MCMC estimation of the Local Learning Coefficient with Timaeus’ Murfet.| The Dan MacKinlay stable of variably-well-consider’d enterprises
As AI and machine learning continue to revolutionize industries, data annotation has emerged as a critical component in the development of intelligent| Zilo AI
Explore the most up-to-date challenges and best practices in data analytics.| Datamation
Banks have been using natural language processing and machine learning applications for years in managing their anti-money laundering and Bank| ABA Banking Journal
So, in 2025, which should you choose: PyTorch for fast-paced AI experimentation or TensorFlow for rock-solid production - and could the real answer be BOTH? The post TensorFlow vs PyTorch: Which Framework Should You Choose in 2025? appeared first on ShiftMag.| ShiftMag
Author(s): Rashmi Originally published on Towards AI. Getting started with workflow Automation n8n is an open-source workflow automation tool that allows you to connect different apps and services together to automate tasks and processes. Think of it as a way to make your various tools “talk to each other” without writing code. AI Automation with n8nThe article discusses the open-source workflow automation tool n8n, detailing its key features, integrations, and practical use cases for aut...| Towards AI
Author(s): EzInsights AI Originally published on Towards AI. Vector databases like Pinecone, Weaviate, Milvus, and FAISS are the backbone of modern AI applications — from RAG (Retrieval-Augmented Generation) to semantic search and recommendation systems. Optimizing them is critical for speed, cost, and accuracy. Here’s a detailed breakdown of 14 key optimization techniques every AI/ML engineer should master: 1. Choose the Right Index Type Why it matters: Different index types balance spee...| Towards AI
Author(s): EzInsights AI Originally published on Towards AI. Artificial Intelligence (AI) has reached a fascinating stage of growth. Large Language Models (LLMs) such as GPT-4, Claude, and LLaMA can generate text, answer questions, write code, and assist with research. Yet, despite their power, most of these models remain passive responders. They are great at conversation but struggle when asked to perform real-world tasks that require reasoning across multiple steps or interacting with exter...| Towards AI
Author(s): Aditya Gupta Originally published on Towards AI. Introduction What would be easier: teaching someone to play the guitar who has already learned the piano, or teaching someone who has never touched a musical instrument? Most of us would agree that the person with piano experience would pick up guitar much faster. They already understand concepts like reading music, rhythm, and finger coordination, which transfer easily to the new instrument. Transfer learning in artificial intellige...| Towards AI
Last Updated on September 30, 2025 by Editorial Team Author(s): Tanmoy Das Originally published on Towards AI. $1,250 followed right after my first AI Gig. This story is about how I became one of the very early adopters of ChatGPT and used it to earn my first $100 without much prior knowledge or expertise on AI. That gig eventually got me $1,350, but the point is… Image created by Google Gemini’s Nano BananaIn the article, the author recounts how he discovered ChatGPT during a layover and...| Towards AI
Last Updated on September 30, 2025 by Editorial Team Author(s): Talib Originally published on Towards AI. Okay, welcome to your third graph. What are we going to do this time? Well, enough processing multiple values and everything. Let’s actually get the graph more complicated. That’s why we’re going to be building a sequential graph. All it all that basically means is we’re going to be creating and handling multiple nodes that can sequentially process and update different parts of th...| Towards AI
Last Updated on September 30, 2025 by Editorial Team Author(s): Devi Originally published on Towards AI. Navigation: Why SLMs on CPUs are Trending When CPUs Make Sense SLMs vs LLMs: A Hybrid Strategy The CPU Inference Tech Stack Hands-On Exercise: Serving a Translation SLM on CPU with llama.cpp + EC2 Why SLMs on CPUs are Trending Traditionally, LLM inference required expensive GPUs. But with recent advancements, CPUs are back in the game for cost-efficient, small-scale inference. Three big sh...| Towards AI
Last Updated on September 30, 2025 by Editorial Team Author(s): Harsh Chandekar Originally published on Towards AI. If you’ve ever asked a large language model (LLM) like GPT or Gemini a question and received a response that sounded too smooth to be wrong — but was completely made up — you’ve met the phenomenon of hallucination. These aren’t hallucinations in the psychedelic sense, but in the sense of confidently fabricated details. Think of your overly confident friend who will inv...| Towards AI
Last Updated on September 30, 2025 by Editorial Team Author(s): Kuriko Iwai Originally published on Towards AI. A step-by-step guide to achieving continuous data integration and delivery in production ML systems Building robust Machine Learning (ML) applications demands meticulous version control for all components: code, models, and the data that powers them. Photo by Mohamed Nohassi on UnsplashThe article explores the complexities of establishing a Data CI/CD pipeline tailored for scalable ...| Towards AI
Author(s): Ali Oraji Originally published on Towards AI. Overfitting is when a neural network (or any ML model) captures noise and characteristics of the tr ...| towardsai.net
In-Context Fine-Tuning for Time-Series: The Next Evolution Beyond Prophet and Traditional Forecasting How Google’s TimesFM-ICF achieves fine-tuned model performance without training – and why this changes everything for production forecasting systems If you’re reading this, you’ve likely wrestled with time-series forecasting in production. Perhaps you’ve implemented Facebook Prophet for its interpretable seasonality decomposition, experimented with […]| DEJAN
RexBERT is a domain-specialized language model trained on massive volumes of e-commerce text (product titles, descriptions, attributes, reviews, FAQs). Unlike general-purpose transformers, it is optimized to understand the quirks of product data and the way consumers phrase queries. For a technical SEO professional, this means better alignment between how search engines interpret product content and […]| DEJAN
Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing industries with smart automation, predictive analytics, and larger scale AI-enabled decisions, but any AI production deployment is only as good as […] The post The Role of Synthetic Data in AI Model Training appeared first on Datafloq.| Datafloq
IBM launches Granite 4.0, its latest enterprise AI model, delivering high performance and cost-efficient solutions for business applications.| AIT365
Ultimately, the quantum computing stack proved 34% better at predicting the likelihood a trade would be filled. The post HSBC, IBM See Potential for Bond-Trading Bonanza in Quantum Test Results appeared first on The Daily Upside.| The Daily Upside
.jpg)
What if every single article on your site could become a revenue engine—without adding manual work or slowing down your team? Learn more in this blog post.| blog.ex.co
I let an AI pick out my outfits using computer vision and pictures of social media fashion influencers.| daleonai.com
I’ve fallen into this pattern where I do an hour or so of self-directed learning in the mornings before going to work. Until recently it was an excellent CMU course on the design of SQL database systems, which I’ve mentioned previously here. I’ve finished that, so I thought I would do something shorter and fun as a break before finding another course to do. I chose The freeCodeCamp.org hot dog or not hot dog tensorflow course. 90 minutes seemed achievable, and I too wish to know if an ...| Made by Mikal
The support we raise through this campaign will provide the foundation for everything we do in FY26. Private support from generous donors like you has become more critical than ever. Thank you for carrying the future of precision nutrition. Your investment drives the science of better health.| UNC NRI
Graduate students at the NRI are uncovering how genetics and multi-omics can transform nutrition into a more precise, preventive, and personal science.| UNC NRI
When it comes to body weight, no single story or strategy fits all. Conversations about weight and health are evolving, as more clinicians and researchers seek to support individuals in ways that reflect both scientific evidence and patient-centered care. In a new commentary published in the Journal of the Academy of Nutrition and Dietetics, UNC Nutrition Research Institute (NRI) researcher Rachel Goode, PhD, MPH, LCSW, and colleagues propose a broadened approach to weight inclusivity. This u...| uncnri.org
Influencer Marketing Expand your reach and engage with your target audience using this trending technique that blends celebrity endorsements with social media marketing. LEARN MORE Leading High Performing Remote Teams How can leaders ensure that performance remains high in remote or hybrid-work environments? Learn More on Design Thinking Learn the 5 phases of this problem-solving methodology […]| GLOBIS Insights
Computer vision is a fast-growing field of science that deals with the extraction of information from digital images and videos to gain a high-level understanding of the environment. The technology is predominantly applied in complex problems in robotics, augmented reality, and self-driving cars, such as object detection, space measurements for navigation, face recognition, action and […] The post Top 10 computer vision frameworks you need to know in 2025 appeared first on RoboticsBiz.| RoboticsBiz
La crescente volatilità globale mette a dura prova le filiere italiane, ancora troppo reattive e poco proattive nella gestione del rischio. Secondo l’Osservatorio Supply Chain Planning del Politecnico di Milano, solo un’azienda su dieci ha piani di contingenza strutturati, mentre meno del 40% delle grandi imprese e appena il 10% delle PMI adotta l’intelligenza artificiale L'articolo Supply chain sotto pressione: l’AI resta la grande occasione mancata delle imprese italiane proviene d...| AI4Business
Zero Trust architecture is a solution for uncontrolled access to network resources. It provides a model for every access request to undergo authorization and authentication before being given the right to use assets. More importantly, while legacy solutions give unhindered access to all resources after access has been granted, zero trust ensures access is only […]| LearnWoo
Join Stephen Paff and Laurie Johnson October 14, starting at 7 p.m. US Central Time, as they discuss the implications the recent AI technology will have on people and society. The session will be live on zoom. You can get in on this conversation by becoming a patron of the Maurin Academy at the Salt of the Earth level or above.| The Maurin Academy for Regenerative Studies
Après ces premières semaines de rentrée, je vous souhaite la bienvenue dans ce troisième article de notre série sur le traitement du langage naturel après avoir vu les n-grams et les embeddings. Au…| enioka
Last summer I sat down with Tom Secunda, who co-founded Bloomberg LP with Mike Bloomberg, to talk about areas of shared philanthropic interest. Tom told me that academic institutions do not have access to the kind of AI/ML infrastructure that the top tech companies have and he wanted to fix that. His idea was a […]| AVC
Author(s): MKWriteshere Originally published on Towards AI. How Apple eliminated the need for separate visual AI systems with one tokenizer that handles all ...| towardsai.net
Healthcare is under pressure as patient volumes are rising, increasing in cost and the necessity to make diagnoses faster requires smart solutions. Traditional software can’t keep up there. What is really changing the game is machine learning in healthcare. Machine learning is already transforming how healthcare software is designed and used, whether it is going […] The post How Machine Learning is Modernizing Healthcare Software Development appeared first on AI Software Development & Cus...| AI Software Development & Custom AI Solutions for Businesses
I gemelli digitali non rappresentano solo macchine, ma anche persone. Nel marketing, permettono di predire, adattare e personalizzare le offerte in tempo reale, migliorando l’efficacia delle campagne promozionali L'articolo Digital Twin del cliente: come anticipare i comportamenti d’acquisto proviene da Agenda Digitale.| Agenda Digitale
A completely hands-on and beginner-friendly deep dive on PySpark using Databricks.| Daily Dose of Data Science
Machine learning has become a major trend in the world of technology. It has the ability to solve problems and| Artificial Intelligence Magazine | AI Webezine
Yushu Xia's research bridges field-based science and advanced modeling to inform more resilient land management strategies that benefit farmers, ranchers, communities and the planet.| State of the Planet
This is a practical guide to help you transform from Machine Learning novice to skilled ML practitioner. Download the first 3 chapters for free!| Data School
IBM releases GraniteDocling, an open-source compact document AI model with improved accuracy, multilingual support, and enterprise readiness| MarkTechPost
You Are Here: Home » 2025 » September| QuickRead | News for the Financial Consulting Professional
Discover the key machine learning fraud prevention benefits.| Signifyd
Getting really good at solving technical problems is just the first step in building complex systems. You can have a team full of brilliant engineers who know everything about coding, electronics, and mathematics, but if they don’t have the right methods for working together on big projects, things can still... Read more » The post Why Complex Projects Need More Than Just Smart Engineers appeared first on Big Data Analytics News.| Big Data Analytics News
Waiting for perfect data can stall your machine learning project and result in losing opportunities of creating good-enough models. The post Applied ML: When ‘perfect’ becomes the enemy of ‘good’ first appeared on TechTalks.| TechTalks
Quantum computers are expected to solve previously unsolvable problems (or ones that would take ages) across industries. The post Quantinuum Trims the Timeline for Quantum Computing appeared first on The Daily Upside.| The Daily Upside
He estado todo el verano investigando, tanto en temas de domotica con python, arquitectura zero trust, software distribuido y big data con scala/spark/java, un proyecto de ciberseguridad en la que descubrí una, en mi opinión, muy grave falla en youtube y en los proveedores de video, pues permite literalmente la exfiltración de información confidencial de…| Aironman techblog
I’ve been researching all summer, both in home automation with Python, zero trust architecture, distributed software and big data with Scala/Spark/Java, a cybersecurity project in which I dis…| Aironman techblog
When you talk to an AI assistant, it can feel like it remembers what you said before. But large language models (LLMs) don’t actually have memory on their own. They don’t remember conversations unless that information is given to them again. So, how ...| freeCodeCamp.org
Singular Learning Theory’s eldest child in practice\| The Dan MacKinlay stable of variably-well-consider’d enterprises
Author(s): Vlad Johnson Originally published on Towards AI. In the rapidly evolving field of Artificial Intelligence, multi-agent systems have emerged as a ...| towardsai.net
Most of the code used in the video: https://github.com/vittoriabitton/nx_hailo/blob/main/nx_hailo/livebooks/remote_device_inference.livemd| Poeticoding
Learn how data observability safeguards your data supply chain—preventing costly errors, downtime, and lost trust in analytics.| blog.powr.io
Futurists insist that AI will soon eclipse the capacities of the most gifted human mind. What hope do we have against superintelligent machines? But we aren’t really on the path to developing intelligent machines. In fact, we don’t even know where that path might be. Source| Books – Discovery Institute
Discover how a former educator turned data storyteller used Python to uncover key factors boosting student math scores, overcoming coding challenges in this inspiring EdTech journey.| Mike's Blog
Announcing The Stargate Project The Stargate Project is a new company which intends to invest...| Mike's Blog
This article in MIT News: “New research shows the natural variability in climate data can cause AI models to struggle at predicting local temperature and rainfall.” … “While…| GeoEnergy Math
Author(s): Shauvik Kumar Originally published on Towards AI. “The goal is to turn data into information, and information into insight.” — Carly Fiorina, for ...| towardsai.net
Realiza un proyecto python de 100 líneas para detectar y seguir personas en video. Usaremos Yolo v8 y Bytetrack. The post Seguimiento de Objetos con Yolo v8 y BYTETrack – Object Tracking first appeared on Aprende Machine Learning.| Aprende Machine Learning
Ya puedes utilizar Stable Diffusion txt2img para crear imágenes en segundos a coste cero desde tu propio ordenador. Aprende a instalarlo y usarlo.| Aprende Machine Learning
In today’s data-driven landscape, organizations are generating unprecedented volumes of data that require sophisticated machine learning solutions capable of processing information at massive scale. Apache Spark ML and Databricks ML have emerged as the leading platforms for distributed machine learning, offering unprecedented capabilities for data scientists and engineers working with big data. This comprehensive guide […] The post Spark ML & Databricks Secrets: Advanced Guide 2025 first ...| Techwards
I’ve just been in Sydney for a couple of days for CloudCon 2025. I think depending on how you count this is my third one of these events — the event has changed names at least twice, so its actually a little hard to work out the lineage of the event. This year’s conference was […]| Made by Mikal
Discover what unified data management is, how it works, and how teams can leverage it to meet their data management needs.| Git for Data - lakeFS
The workflow that's changing how software gets built.| Braintrust
The post Neel Nanda on the race to read AI minds appeared first on 80,000 Hours.| 80,000 Hours
Author(s): Padmaja Kulkarni Originally published on Towards AI. When most teams talk about “AI or data risk,” the conversation always drifts toward accuracy ...| towardsai.net
| UNC NRI
This in-person Appetite for Life event will take you inside the kitchen to explore simple, seasonal recipes that are both delicious and nutritionally balanced.| UNC NRI
Join us virtually on October 15 at noon for our version of the popular 3-Minute Thesis competition!| UNC NRI
TL;DR: Search engines and Search Engine Optimization (SEO) have come a long way from simple keyword matching and text-based optimization. With Artificial| GLOBIS Insights
AI in data cleaning offers an added advantage in adaptability, automation, consistency, and reliability. Contact us to clean your raw data.| www.expressanalytics.com
Build a regime-adaptive trading strategy in Python with this hands-on guide. Detect market regimes using Hidden Markov Models and generate signals with Random Forests—all with complete code and walk-forward backtesting.| Quantitative Finance & Algo Trading Blog by QuantInsti
Explore how Bayesian statistics helps traders update beliefs, build adaptive models, and manage risk. Learn Bayes’ Theorem, Naive Bayes, Bayesian inference, and their applications in algorithmic trading and quantitative finance.| Quantitative Finance & Algo Trading Blog by QuantInsti
Explore how linear regression powers trading strategies in quantitative finance. Understand OLS, model assumptions, Python code for stock prediction, and real-world use cases for building and evaluating trading models.| Quantitative Finance & Algo Trading Blog by QuantInsti
Build classification trading strategy in Python for predicting the S&P500 price from scratch. Learn how to handle binary and multiclass problems using key ML algorithms like SVM, with a full coding workflow—from data prep and training to evaluation and visualization.| Quantitative Finance & Algo Trading Blog by QuantInsti
Explore the bias-variance tradeoff in machine learning for trading strategies. Learn how to build and backtest a trading model using PCA, VIF, and bias-variance decomposition to optimize performance and mitigate overfitting.| Quantitative Finance & Algo Trading Blog by QuantInsti
Learn how reinforcement learning is applied in stock trading with Q-learning, experience replay, and advanced techniques. Explore its edge over traditional ML in building trading strategies.| Quantitative Finance & Algo Trading Blog by QuantInsti
After suffering massive outflows, Asia’s quant firms are outperforming again, especially in China.| Digital Finance
Posted by Colby Banbury, Emil Njor, Andrea Mattia Garavagno, Vijay Janapa Reddi – Harvard UniversityTinyML is an exciting frontier in machine learning, enabling models to run on extremely low-power devices such as microcontrollers and edge devices. However, the growth of this field has been stifled by a lack of tailored large and high-quality datasets. That's where Wake Vision comes in—a new dataset designed to accelerate research and development in TinyML.| The TensorFlow Blog
Posted by Jason Jabbour, Kai Kleinbard and Vijay Janapa Reddi (Harvard University)Everyone wants to do the modeling work, but no one wants to do the engineering.| The TensorFlow Blog
Posted by Sharbani Roy – Senior Director, Product Management, Google | The TensorFlow Blog
Posted by Terence Parr, GoogleDecision trees are the fundamental building block of Gradient Boosted Trees and Random Forests, the two most popular machine learning models for tabular data. To learn how decision trees work and how to interpret your models, visualization is essential.| The TensorFlow Blog
Russell Kaplan talks about data-centric AI in practice and what he's learned at scale AI, working with hundreds of CV teams, about what it takes to make machine learning work well in production.| AI Accelerator Institute
How we used generative AI to build our year-in-review campaign| Canva - Engineering Blog
Qualitative comparison of image embedding models to power a scalable similar-image replacement system for Canva designs.| Canva - Engineering Blog