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Claude 4’s “whistle-blow” surprise shows why agentic AI risk lives in prompts and tool access, not benchmarks. Learn the 6 controls every enterprise must adopt.
Rose Yu has drawn on the principles of fluid dynamics to improve deep learning systems that predict traffic, model the climate, and stabilize drones during flight.
You vs. AI, offline AI, Gemini tricks, AI influencers, 3D film agents, and more...
As we look ahead, the relationship between engineers and AI systems will likely evolve from tool and user to something more symbiotic.
Micro Center, an electronics retailer, has opened a store in Silicon Valley in California And so the nerd kingdom has returned.
If you use Google’s apps and AI, it’s worth looking at this all-inclusive service. We break down the plans and how much they cost.
Fighting robots, language partners, flattery bots, legendary offers, and more...
Alibaba's QwenLong-L1 helps LLMs deeply understand long documents, unlocking advanced reasoning for practical enterprise applications.
With Conversational AI 2.0, ElevenLabs aims to provide tools and infrastructure for truly intelligent, context-aware enterprise voice agents.
This is how to use the attention mechanism in a time series classification framework
The post Hands-On Attention Mechanism for Time Series Classification, with Python appeared first on Towards Data Science.
Lessons learnt using LlamaIndex and Modal
The post Agentic RAG Applications: Company Knowledge Slack Agents appeared first on Towards Data Science.
Customer support is a data goldmine. Here’s how to unlock its full potential with data science.
The post The Secret Power of Data Science in Customer Support appeared first on Towards Data Science.
Introducing the AI strategy playbook
The post Gaining Strategic Clarity in AI appeared first on Towards Data Science.
Google is investing an additional $7 billion in Iowa within the next two years in cloud and AI infrastructure, as well as in expanded workforce development programs, mea…
Scalable fine-tuning techniques for large language models
The post LLM Optimization: LoRA and QLoRA appeared first on Towards Data Science.
This architecture lets Token Monster tap into a range of models from different providers without having to build separate integrations for each one.
Visualize flood impact using elevation data
The post Simulating Flood Inundation with Python and Elevation Data: A Beginner’s Guide appeared first on Towards Data Science.
Key steps to using RAG for generating MCQs from Wikipedia articles based on user-defined context
The post How to Build an MCQ App appeared first on Towards Data Science.
In this post you define, deploy, and provision a SageMaker Project custom template purely in Terraform. With no dependencies on other IaC tools, you can now enable SageMaker Projects strictly within your Terraform Enterprise infrastructure.
ZURU collaborated with AWS Generative AI Innovation Center and AWS Professional Services to implement a more accurate text-to-floor plan generator using generative AI. In this post, we show you why a solution using a large language model (LLM) was chosen. We explore how model selection, prompt engineering, and fine-tuning can be used to improve results.
Non-conversational applications offer unique advantages such as higher latency tolerance, batch processing, and caching, but their autonomous nature requires stronger guardrails and exhaustive quality assurance compared to conversational applications, which benefit from real-time user feedback and supervision. This post examines four diverse Amazon.com examples of such generative AI applications.
In this post, we give an overview of a well-established generative AI foundation, dive into its components, and present an end-to-end perspective. We look at different operating models and explore how such a foundation can operate within those boundaries. Lastly, we present a maturity model that helps enterprises assess their evolution path.
OpenSearch offers a wide range of third-party machine learning (ML) connectors to support this augmentation. This post highlights two of these third-party ML connectors. The first connector we demonstrate is the Amazon Comprehend connector. In this post, we show you how to use this connector to invoke the LangDetect API to detect the languages of ingested documents. The second connector we demonstrate is the Amazon Bedrock connector to invoke the Amazon Titan Text Embeddings v2 model so that you can create embeddings from ingested documents and perform semantic search.
Amazon Bedrock Model Copy and Model Share features provide a powerful option for managing the lifecycle of an AI application from development to production. In this comprehensive blog post, we'll dive deep into the Model Share and Model Copy features, exploring their functionalities, benefits, and practical applications in a typical development-to-production scenario.
Build and fine-tune XGBoost models entirely online — no installations, just data, tuning, and results inside your browser.
Two years after Sam Altman pitched Congress on AI guardrails, he's back in Washington with a new message: To beat China, invest in OpenAI.
A selection of our most-read and -shared articles of the past month
The post May Must-Reads: Math for Machine Learning Engineers, LLMs, Agent Protocols, and More appeared first on Towards Data Science.
The photo gallery app in Honor’s latest midrange phones has an image-to-video generative AI feature powered by Google. It’ll probably come to your phone soon.
In this article, we will learn how to create an ETL pipeline using DuckDB.
Back in April, OpenAIannounced it was rolling back an update to its GPT-4o model that made ChatGPT’s responses to user queries too sycophantic. An AI model that acts in an overly agreeable and flattering way is more than just annoying. It could reinforce users’ incorrect beliefs, mislead people, and spread misinformation that can be dangerous—a…