Building Intelligent iOS Apps with Apple’s Foundation Models Framework
The iOS development world has undergone a radical change. Only a few years back, implementing AI functionalities required costly cloud APIs or, at best, on-device processing with limited capabilities. The introduction of Apple’s Foundation Models framework heralds the availability of a 3 billion par...
Synthesia hits $4B valuation, lets employees cash out
British startup Synthesia, whose AI platform helps companies create interactive training videos, has raised a $200 million Series E round of funding that brings its valuation to $4 billion — up from $2.1 billion just a year ago.
SycoEval-EM: Sycophancy Evaluation of Large Language Models in Simulated Clinical Encounters for Emergency Care
arXiv:2601.16529v1 Announce Type: new
Abstract: Large language models (LLMs) show promise in clinical decision support yet risk acquiescing to patient pressure for inappropriate care. We introduce SycoEval-EM, a multi-agent simulation framework evaluating LLM robustness through adversarial patient ...
Doc2AHP: Inferring Structured Multi-Criteria Decision Models via Semantic Trees with LLMs
arXiv:2601.16479v1 Announce Type: new
Abstract: While Large Language Models (LLMs) demonstrate remarkable proficiency in semantic understanding, they often struggle to ensure structural consistency and reasoning reliability in complex decision-making tasks that demand rigorous logic. Although class...
DSGym: A Holistic Framework for Evaluating and Training Data Science Agents
arXiv:2601.16344v1 Announce Type: new
Abstract: Data science agents promise to accelerate discovery and insight-generation by turning data into executable analyses and findings. Yet existing data science benchmarks fall short due to fragmented evaluation interfaces that make cross-benchmark compari...
SemanticALLI: Caching Reasoning, Not Just Responses, in Agentic Systems
arXiv:2601.16286v1 Announce Type: new
Abstract: Agentic AI pipelines suffer from a hidden inefficiency: they frequently reconstruct identical intermediate logic, such as metric normalization or chart scaffolding, even when the user's natural language phrasing is entirely novel. Conventional boundar...
When Agents Fail to Act: A Diagnostic Framework for Tool Invocation Reliability in Multi-Agent LLM Systems
arXiv:2601.16280v1 Announce Type: new
Abstract: Multi-agent systems powered by large language models (LLMs) are transforming enterprise automation, yet systematic evaluation methodologies for assessing tool-use reliability remain underdeveloped. We introduce a comprehensive diagnostic framework tha...
Analyzing Neural Network Information Flow Using Differential Geometry
arXiv:2601.16366v1 Announce Type: new
Abstract: This paper provides a fresh view of the neural network (NN) data flow problem, i.e., identifying the NN connections that are most important for the performance of the full model, through the lens of graph theory. Understanding the NN data flow provide...
StepFun AI Introduce Step-DeepResearch: A Cost-Effective Deep Research Agent Model Built Around Atomic Capabilities
StepFun has introduced Step-DeepResearch, a 32B parameter end to end deep research agent that aims to turn web search into actual research workflows with long horizon reasoning, tool use and structured reporting. The model is built on Qwen2.5 32B-Base and is trained to act as a single agent that pla...
A Coding Implementation to Automating LLM Quality Assurance with DeepEval, Custom Retrievers, and LLM-as-a-Judge Metrics
We initiate this tutorial by configuring a high-performance evaluation environment, specifically focused on integrating the DeepEval framework to bring unit-testing rigor to our LLM applications. By bridging the gap between raw retrieval and final generation, we implement a system that treats model ...
Quiet Revolutions in AI: Unsung Innovators Building Practical, Local Solutions Beyond Silicon Valley
Small teams, community labs, and regionally focused platforms are quietly building practical, deployable AI that solves everyday problems—health screening, local‑language NLP, supply‑chain reliability and farm mechanization—yet these advances rarely make global headlines. This article spotlights tho...
Researchers tested AI against 100,000 humans on creativity
A massive new study comparing more than 100,000 people with today’s most advanced AI systems delivers a surprising result: generative AI can now beat the average human on certain creativity tests. Models like GPT-4 showed strong performance on tasks designed to measure original thinking and idea gen...
How UX Research Methods Reveal Hidden AI Orchestration Failures in Enterprise Collaboration Agents
I have spent the last several years watching enterprise collaboration tools get smarter. Join a video call today, and there’s a good chance five or six AI agents are running simultaneously: transcription, speaker identification, captions, summarization, task extraction. On the product side of it, ea...
We live in a world where answers are instant. AI copilots, search engines, short videos, and interactive courses can explain almost anything in minutes. Information is no longer scarce. What is scarce is depth, clarity, and the ability to connect ideas into sound decisions. That is where books still...
Legal AI giant Harvey acquires Hexus as competition heats up in legal tech
Hexus founder and CEO Sakshi Pratap, who previously held engineering roles at Walmart, Oracle, and Google, tells TechCrunch that her San Francisco-based team has already joined Harvey, while the startup's India-based engineers will come onboard once Harvey establishes a Bangalore office.
GitHub Releases Copilot-SDK to Embed Its Agentic Runtime in Any App
GitHub has opened up the internal agent runtime that powers GitHub Copilot CLI and exposed it as a programmable SDK. The GitHub Copilot-SDK, now in technical preview, lets you embed the same agentic execution loop into any application so the agent can plan, invoke tools, edit files, and run commands...
How an AI Agent Chooses What to Do Under Tokens, Latency, and Tool-Call Budget Constraints?
In this tutorial, we build a cost-aware planning agent that deliberately balances output quality against real-world constraints such as token usage, latency, and tool-call budgets. We design the agent to generate multiple candidate actions, estimate their expected costs and benefits, and then select...
The World Economic Forum’s annual meeting in Davos felt different this year, and not just because Meta and Salesforce took over storefronts on the main promenade. AI dominated the conversation in a way that overshadowed traditional topics like climate change and global poverty, and the CEOs weren’t ...
Optimizing Data Transfer in Distributed AI/ML Training Workloads
A deep dive on data transfer bottlenecks, their identification, and their resolution with the help of NVIDIA Nsight™ Systems – part 3
The post Optimizing Data Transfer in Distributed AI/ML Training Workloads appeared first on Towards Data Science.
The World Economic Forum’s annual meeting in Davos felt different this year, and not just because Meta and Salesforce took over storefronts on the main promenade. AI dominated the conversation in a way that overshadowed traditional topics like climate change and global poverty, and the CEOs weren’t ...