Visa ChatGPT integration enables AI agent retail purchasing
Visa has linked its payment infrastructure to ChatGPT, enabling AI agents to recommend retail products and execute financial transactions. The deployment removes human intervention from the final stages of the retail funnel. Autonomous agents will now process user prompts, evaluate merchant catalogues, and complete the checkout process using Visa’s payment rails at any supporting merchant. […]
Xebia: On building the data foundation for AI agents – and then accelerating
If your remit is to help your organisation add AI agents to accelerate its processes, you have to start at the foundation – and that means making your data available for AI consumption. Agentic AI scales on data strength, as Niels Zeilemaker, global CTO at Xebia, explains. “If you don’t think about that, you can […]
Nous Research Ships Hermes Agent Profile Builder: Identity, Model, Skills, and MCP Servers in One Dashboard Flow
Nous Research · Hermes Agent The Profile Builder, explained DEMOsimulation, not the live product Provider OpenRouterNous PortalNVIDIAOpenAI-compatible (custom) Built-in toolsets Off → written to agent.disabled_toolsets. MCP servers FilesystemGitHubHTTP + Add mcp_servers is a map keyed by server name. ~/.hermes/profiles/researcher/config.yaml Copy Source link
Meet ‘North Mini Code’: Cohere’s 30B Open-Weight Mixture-of-Experts Model With 3B Active Parameters for Agentic Coding
This week, Cohere AI team shipped its first developer-facing coding model named ‘North Mini Code‘. ‘North Mini Code’ is open-weight and focused at software engineers. It is a mixture-of-experts (MoE) model with 30B total parameters. Only 3B of those parameters activate per token. The release is positioned around “sovereign” AI. The idea is simple: run […]
A Coding Implementation on Microsoft SkillOpt for Instrumented Prompt Optimization, Skill Evolution Analysis, and Baseline Comparison
k = RUN_KNOBS train_out = run_cli([“python”,”scripts/train.py”,”–config”,CFG,”–split_dir”,SPLIT, “–optimizer_model”,OPTIMIZER_MODEL,”–target_model”,TARGET_MODEL,”–out_root”,RUN, *COMMON, “train.train_size=0″, f”train.num_epochs={k[‘num_epochs’]}”, f”train.batch_size={k[‘batch_size’]}”, f”gradient.minibatch_size={k[‘minibatch’]}”, f”gradient.merge_batch_size={k[‘merge_batch’]}”, f”gradient.analyst_workers={k[‘workers’]}”, f”optimizer.learning_rate={k[‘lr’]}”, f”optimizer.lr_scheduler={k[‘lr_sched’]}”, “optimizer.use_slow_update=true”, “optimizer.use_meta_skill=true”, f”env.workers={k[‘workers’]}”, f”env.limit={k[‘limit’]}”], “TRAIN (rollout->reflect->aggregate->select->update->gate; slow-update + meta-skill)”) import pandas as pd, matplotlib.pyplot as plt hist = json.loads(pathlib.Path(f”{RUN}/history.json”).read_text()) df = pd.json_normalize(hist) print(“\nhistory.json columns:”, list(df.columns)) def col(*cands): for c in cands: for actual in df.columns: if c in actual.lower(): […]
Google AI Releases DiffusionGemma, a 26B MoE Open Model Using Text Diffusion for Up to 4x Faster Generation
Google AI team including the Google DeepMind researchers have just released DiffusionGemma, an experimental open model for text generation. It uses text diffusion instead of standard autoregressive decoding. The model ships under a permissive Apache 2.0 license. Google positions it for devs and researchers exploring speed-critical, interactive local workflows. Examples include in-line editing, rapid iteration, […]
How to Refactor Code with Claude Code
are amazing at quickly implementing a lot of code. However, if you’ve ever worked a lot with coding agents, you’ll notice they start struggling after a while. Maybe you’ve spent a few days writing code with AI. Everything went perfectly and fast, and then you start noticing the tasks take longer, and the AI is […]
How to Train a Scoring Model in the Age of Artificial Intelligence
All code used in this section is available on GitHub. The business logic and modeling functions are located in the src/selection directory, specifically in the following file: src/selection/logit_model_selection.py The corresponding analysis and results are documented in: 08_logistic_model_selection.qmd , it has become easier to generate code, automate model training, compare metrics, and produce summary tables. A […]
Beyond extract_text: The Two Layers of a PDF That Drive RAG Quality
in a RAG process, the parser has one job. Read the document the way a human would before answering a question about it. What is this thing? A CV, an insurance contract, a regulatory text, an academic paper? How many pages? Born digital or scanned, or stitched together from both? What does it carry: paragraphs, […]
Bayesian Networks and Markov Networks: An Intuitive Guide to Structured Uncertainty
explanations begin with prediction. A churn model estimates whether a customer is likely to leave. A fraud model estimates whether a transaction is suspicious. A diagnosis model estimates the likelihood of a condition from symptoms, tests and history. A document classifier assigns a category from text, metadata or embeddings. In each case, the setup is […]