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China’s MiniMax launches M1 for GPT‑4‑level reasoning at half the cost
IBM debuts unified agent governance/security software
Intel hires new engineering leaders aimed at its AI comeback
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NEWS UPDATES
China’s MiniMax Releases GPT‑4‑Level Model at Half the Cost
Chinese AI startup MiniMax has released M1, an open-source hybrid‑attention reasoning model with record‑breaking context length and strong cost efficiency—training ran at about $535,000, reportedly less than 1% of GPT-4’s cost.
This opens up new options for companies exploring open-source AI. Leaders can start testing models like M1 to reduce costs and avoid being tied to major cloud providers.
IBM Rolls Out Tool to Manage AI Agents Safely
IBM has launched a tool that helps businesses manage the safety and rules around AI agents. It combines security checks, compliance tracking, and agent monitoring in one place.
As more teams start using AI agents, it becomes easier to stay compliant and avoid risks without building a system from scratch.
Intel Brings In New Engineering Leaders for AI Efforts
Intel has hired new engineering leaders to strengthen its AI plans. The team includes experts in chips, systems, and customer needs.
This signals Intel’s push to get back in the AI race. Companies using their hardware can expect faster updates and stronger support.
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STRATEGIC AI DECISION
IBM just launched a tool to solve which fast-growing challenge in AI adoption?
PS. You just read the answer in the news above :)
MARKET
💰 Funding
Maven AGI raised $50M to build an enterprise-grade AI platform.
SportsVisio secured $3.2M to develop AI tools for athletes and fan engagement.
💼 Who’s Hiring in AI
Machine Learning Engineer at Zus Health (US)
Software Engineer (ML Infra) at Blue Rose Research (Remote)
🐦 Github Repo to Design in < 1 min
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9:33 PM • Jun 18, 2025
PROMPT TUTORIAL
Comprehensive Governance Framework
You are the AI Governance Lead at a [Company Size]/[Industry] deploying AI agents across the business. Draft a comprehensive governance framework covering multiple agent types, such as chatbots, schedulers, and analytics bots. For each, define the business use case, the responsible owner, and the data it accesses. Identify key risks like data exposure, non-compliance, or misuse, and map them to the relevant regulations (e.g., GDPR, SOX, EU AI Act). Suggest technical controls such as input filtering, audit logging, red-teaming frequency, and model retraining intervals. Recommend a review cycle with cross-functional roles from legal, IT, and operations, and outline a cadence for internal audits.
Present the output in a table format: Agent | Use Case | Risks | Controls | Owners | Review Schedule. Finish with a 3-point executive summary highlighting readiness level and next steps.
Organization Type/Team: [Insert here]
P.S. You can still get the Prompting Playbook (free for you)
Stay curious, {{first_name | leaders}}
PS. If you missed yesterday’s issue, you can find it here.