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Pentagon Adopts Google Gemini. Deepseek Trains with Blackwell Chips. Meta Closes Avocado Model. Google Launches MCP Servers.
Why the Pentagon is suddenly relying on Google Gemini.Deepseek is supposed to use thousands of smuggled Nvidia chips for AI training.Meta plans a closed AI model 'Avocado' and breaks with its open-source line.Google launches managed MCP servers that let AI agents simply plug into its tools
The AI news for December 11th, 2025
--- This episode is sponsored by ---
Find our more about our today's sponsor Pickert at pickert.de.
---
Would you like to create your own AI-generated and 100% automated podcast on your chosen topic? --> Reach out to us, and we’ll make it happen.
Here are the details of the day's selected top stories:
Why the Pentagon is suddenly relying on Google Gemini.
Source: https://www.all-ai.de/news/top-news24/google-pentagon
Why did we choose this article?
High-impact development: a major practical example of how generative AI is moving into government operations. Important for listeners because it shows vendor positioning, procurement and security trade-offs, and clarifies use cases (back-office, analytics) rather than autonomous weapons — practical consequences for suppliers, regulators, and enterprise adopters.
Deepseek is supposed to use thousands of smuggled Nvidia chips for AI training.
Source: https://the-decoder.de/deepseek-soll-tausende-geschmuggelte-nvidia-chips-fuers-ki-training-nutzen/
Why did we choose this article?
Geopolitically charged supply-chain story with direct implications for model capabilities, export controls, and enforcement. Useful for practitioners and policymakers tracking where advanced compute is actually deployed and the risks around illicit hardware flows.
Meta plans a closed AI model 'Avocado' and breaks with its open-source line.
Source: https://the-decoder.de/meta-plant-geschlossenes-ki-modell-avocado-und-bricht-mit-seiner-open-source-linie/
Why did we choose this article?
Strategic shift at a major platform: Meta moving from open-source to a closed model changes competitive dynamics, access to state-of-the-art models, and the ecosystem for researchers and startups. Practical takeaway: expect tighter control over model capabilities, monetization, and integration paths.
Google launches managed MCP servers that let AI agents simply plug into its tools
Source: https://techcrunch.com/2025/12/10/google-is-going-all-in-on-mcp-servers-agent-ready-by-design/
Why did we choose this article?
Concrete infrastructure move that lowers friction for building tool-enabled AI agents. For developers and product teams this signals easier integrations with Google services (Maps, BigQuery), and a path to more capable, reliable agent behavior — a practical lead indicator for agent-powered products.
Do you have any questions, comments, or suggestions for improvement? We welcome your feedback at [email protected].
--- This episode is sponsored by ---
Find our more about our today's sponsor Pickert at pickert.de.
---
Would you like to create your own AI-generated and 100% automated podcast on your chosen topic? --> Reach out to us, and we’ll make it happen.
Here are the details of the day's selected top stories:
Why the Pentagon is suddenly relying on Google Gemini.
Source: https://www.all-ai.de/news/top-news24/google-pentagon
Why did we choose this article?
High-impact development: a major practical example of how generative AI is moving into government operations. Important for listeners because it shows vendor positioning, procurement and security trade-offs, and clarifies use cases (back-office, analytics) rather than autonomous weapons — practical consequences for suppliers, regulators, and enterprise adopters.
Deepseek is supposed to use thousands of smuggled Nvidia chips for AI training.
Source: https://the-decoder.de/deepseek-soll-tausende-geschmuggelte-nvidia-chips-fuers-ki-training-nutzen/
Why did we choose this article?
Geopolitically charged supply-chain story with direct implications for model capabilities, export controls, and enforcement. Useful for practitioners and policymakers tracking where advanced compute is actually deployed and the risks around illicit hardware flows.
Meta plans a closed AI model 'Avocado' and breaks with its open-source line.
Source: https://the-decoder.de/meta-plant-geschlossenes-ki-modell-avocado-und-bricht-mit-seiner-open-source-linie/
Why did we choose this article?
Strategic shift at a major platform: Meta moving from open-source to a closed model changes competitive dynamics, access to state-of-the-art models, and the ecosystem for researchers and startups. Practical takeaway: expect tighter control over model capabilities, monetization, and integration paths.
Google launches managed MCP servers that let AI agents simply plug into its tools
Source: https://techcrunch.com/2025/12/10/google-is-going-all-in-on-mcp-servers-agent-ready-by-design/
Why did we choose this article?
Concrete infrastructure move that lowers friction for building tool-enabled AI agents. For developers and product teams this signals easier integrations with Google services (Maps, BigQuery), and a path to more capable, reliable agent behavior — a practical lead indicator for agent-powered products.
Do you have any questions, comments, or suggestions for improvement? We welcome your feedback at [email protected].
View all episodes
By Pickert GmbHWhy the Pentagon is suddenly relying on Google Gemini.Deepseek is supposed to use thousands of smuggled Nvidia chips for AI training.Meta plans a closed AI model 'Avocado' and breaks with its open-source line.Google launches managed MCP servers that let AI agents simply plug into its tools
The AI news for December 11th, 2025
--- This episode is sponsored by ---
Find our more about our today's sponsor Pickert at pickert.de.
---
Would you like to create your own AI-generated and 100% automated podcast on your chosen topic? --> Reach out to us, and we’ll make it happen.
Here are the details of the day's selected top stories:
Why the Pentagon is suddenly relying on Google Gemini.
Source: https://www.all-ai.de/news/top-news24/google-pentagon
Why did we choose this article?
High-impact development: a major practical example of how generative AI is moving into government operations. Important for listeners because it shows vendor positioning, procurement and security trade-offs, and clarifies use cases (back-office, analytics) rather than autonomous weapons — practical consequences for suppliers, regulators, and enterprise adopters.
Deepseek is supposed to use thousands of smuggled Nvidia chips for AI training.
Source: https://the-decoder.de/deepseek-soll-tausende-geschmuggelte-nvidia-chips-fuers-ki-training-nutzen/
Why did we choose this article?
Geopolitically charged supply-chain story with direct implications for model capabilities, export controls, and enforcement. Useful for practitioners and policymakers tracking where advanced compute is actually deployed and the risks around illicit hardware flows.
Meta plans a closed AI model 'Avocado' and breaks with its open-source line.
Source: https://the-decoder.de/meta-plant-geschlossenes-ki-modell-avocado-und-bricht-mit-seiner-open-source-linie/
Why did we choose this article?
Strategic shift at a major platform: Meta moving from open-source to a closed model changes competitive dynamics, access to state-of-the-art models, and the ecosystem for researchers and startups. Practical takeaway: expect tighter control over model capabilities, monetization, and integration paths.
Google launches managed MCP servers that let AI agents simply plug into its tools
Source: https://techcrunch.com/2025/12/10/google-is-going-all-in-on-mcp-servers-agent-ready-by-design/
Why did we choose this article?
Concrete infrastructure move that lowers friction for building tool-enabled AI agents. For developers and product teams this signals easier integrations with Google services (Maps, BigQuery), and a path to more capable, reliable agent behavior — a practical lead indicator for agent-powered products.
Do you have any questions, comments, or suggestions for improvement? We welcome your feedback at [email protected].
--- This episode is sponsored by ---
Find our more about our today's sponsor Pickert at pickert.de.
---
Would you like to create your own AI-generated and 100% automated podcast on your chosen topic? --> Reach out to us, and we’ll make it happen.
Here are the details of the day's selected top stories:
Why the Pentagon is suddenly relying on Google Gemini.
Source: https://www.all-ai.de/news/top-news24/google-pentagon
Why did we choose this article?
High-impact development: a major practical example of how generative AI is moving into government operations. Important for listeners because it shows vendor positioning, procurement and security trade-offs, and clarifies use cases (back-office, analytics) rather than autonomous weapons — practical consequences for suppliers, regulators, and enterprise adopters.
Deepseek is supposed to use thousands of smuggled Nvidia chips for AI training.
Source: https://the-decoder.de/deepseek-soll-tausende-geschmuggelte-nvidia-chips-fuers-ki-training-nutzen/
Why did we choose this article?
Geopolitically charged supply-chain story with direct implications for model capabilities, export controls, and enforcement. Useful for practitioners and policymakers tracking where advanced compute is actually deployed and the risks around illicit hardware flows.
Meta plans a closed AI model 'Avocado' and breaks with its open-source line.
Source: https://the-decoder.de/meta-plant-geschlossenes-ki-modell-avocado-und-bricht-mit-seiner-open-source-linie/
Why did we choose this article?
Strategic shift at a major platform: Meta moving from open-source to a closed model changes competitive dynamics, access to state-of-the-art models, and the ecosystem for researchers and startups. Practical takeaway: expect tighter control over model capabilities, monetization, and integration paths.
Google launches managed MCP servers that let AI agents simply plug into its tools
Source: https://techcrunch.com/2025/12/10/google-is-going-all-in-on-mcp-servers-agent-ready-by-design/
Why did we choose this article?
Concrete infrastructure move that lowers friction for building tool-enabled AI agents. For developers and product teams this signals easier integrations with Google services (Maps, BigQuery), and a path to more capable, reliable agent behavior — a practical lead indicator for agent-powered products.
Do you have any questions, comments, or suggestions for improvement? We welcome your feedback at [email protected].