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Midweek Fellows, but that's no reason to start getting lazy and delegating all your work to AI agents; they expose your sensitive data more than you may think, and they don't truly think. OpenAI makes a U-turn and releases an open model you can run locally, while the government makes it even easier for three tech behemoths to land AI federal contracts. Let's dive in and, as always, stay curious.

• OpenAI Releases First Open-Weight Models in 5 Years

• US Government Approves AI Companies for Federal Contracts

• AI Tools

• AI Agents Become New Security, Weak Link

• Learning Corner - Personal Prompt

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OpenAI Releases First Open-Weight Models in 5 Years

OpenAI has released two open-weight language models, gpt-oss-120b and gpt-oss-20b, marking its first such release since GPT-2 in 2019. These models can run locally on consumer devices and be fine-tuned for specific purposes, representing a strategic shift for the company.

Key Features:

• Both models use chain-of-thought reasoning (similar to OpenAI's o1 model)

• Can browse the web, execute code, and function as AI agents

• The smaller 20b model runs on devices with 16GB+ memory

• Available free on Hugging Face under Apache 2.0 license (allowing commercial use)

Performance & Competition:

• OpenAI says gpt-oss-120b performs similarly to its proprietary o3 and o4-mini models

• The release appears to be a response to DeepSeek's recent open-weight model that stunned Silicon Valley

• Positions OpenAI to compete with Meta's Llama series in the open-weight space

CEO Sam Altman emphasized wanting open AI innovation to happen in the US "based on democratic values." The company sees these open models as complementary to its paid services rather than competition, offering advantages like offline operation and firewall compatibility. The release was delayed for additional safety testing, including evaluations of potential misuse by bad actors.

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🧠 Learning Corner

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US Government Approves AI Companies for Federal Contracts

The General Services Administration (GSA) is adding OpenAI's ChatGPT, Google's Gemini, and Anthropic's Claude to its approved vendor list, enabling widespread AI adoption across civilian federal agencies.

Federal agencies can now quickly procure these AI tools through the GSA's Multiple Award Schedule without months of individual negotiations. The GSA used its buying power to secure deep discounts, similar to existing deals with Adobe and Salesforce.

AI will penetrate every inch of our digital world as agencies plan to use AI for processing patent applications, detecting tax fraud, reviewing grant submissions, developing customer service chatbots, and summarizing public comments on regulations. The Treasury Department and Office of Personnel Management have already expressed interest.

The approval comes days after President Trump signed executive orders mandating federal agencies only procure language models "free from ideological bias." GSA officials say enforcing the ban on "woke AI" will be handled agency-by-agency, while emphasizing the US needs to win the AI race.

GSA says more AI vendors will be considered; these three were simply furthest along in procurement.

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AI Agents Become New Security Weak Link

New studies reveal major AI vulnerabilities: LLMs provide incorrect login URLs one-third of the time, while AI agents operate with full user privileges but zero security awareness.

• AI agents (used by 79% of organizations) have access to all enterprise apps and passwords, but can't recognize security threats

• When asked for sign-in URLs, LLMs return wrong sites 34% of the time, including fake, parked, or unrelated domains

• Smaller brands are hit harder as LLMs are more likely to "hallucinate" their login pages

AI agents have the same system privileges as human users, including access to all logins and passwords, but lack the security awareness that comes from employee training. They blindly complete tasks without recognizing threats. Worse, storing these credentials on agent servers means your sensitive data is exposed to those platforms and any third parties with cloud access, multiplying the attack surface.

We suggest implementing browser-native detection for malicious activity and restricting agent permissions immediately. Long-term, develop systems that differentiate between human and AI users in real-time. Most critically: never delegate personal or highly sensitive access to AI agents. They aren't human, won't exercise judgment, and can't be trained to recognize when they're being exploited.