Andy Frenzy

Andy Frenzy 🚀 Exploring the Future with AI With a background in green energy technology and entrepreneurship. But he is a member of the NIO User advisory Board in Sweden.

Andy Frenzy is a dynamic and visionary social media influencer and blogger with a passion for creating a better world through innovative ideas and practices. Andy is dedicated to sharing his knowledge and insights with his followers and empowering them to make a positive impact in their own lives and communities. Whether through his captivating blog posts or thought-provoking social media content,

Andy's mission is to inspire, educate, and bring people together to build a more sustainable and equitable world. Join Andy on this exciting journey as he explores the intersection of technology, sustainability, and entrepreneurship. Disclaimer:
This page is for awareness and informational purposes only. Andy Frenzy is not affiliated with NIO, the Chinese electric car maker. Andy is not a financial advisor, and the views and opinions expressed on this page should not be considered financial advice. All content shared on this page is based on Andy's personal research and experiences, and should not be taken as a guarantee of any kind. It is always important to do your own research and due diligence before making any financial decisions. Although Andy has taken reasonable steps to ensure the accuracy of the information on this page, there may be errors or inaccuracies. As such, it is recommended to double-check all information before relying on it.

01/12/2025

🔥 For anyone wondering where “consciousness” in AI actually lives, here’s the closest thing to seeing inside an LLM’s mind

If you’ve ever tried to explain how AI “thinks,” this is the most beautiful and accurate visualization I’ve seen so far. It’s an interactive 3D fly-through of an LLM’s internal computation based on Llama, but the principles apply to every transformer model.

• Each plane is a tensor, a snapshot of the model’s state as it transforms input into meaning
• Every layer shows the exact mathematical operation being applied (attention, projection, normalization, MLP transformations)
• Click on the right panel to see clear explanations of why that operation produces the next state
• The whole fly-through feels like watching the “internal movie” of a model processing thought

It’s the closest thing we have to a visual answer for: Where does the “soul” of an LLM actually live?

🔥 If you've been wondering how China was able to train its models without NVIDIA chips: they did it abroad.Chinese AI gi...
01/12/2025

🔥 If you've been wondering how China was able to train its models without NVIDIA chips: they did it abroad.

Chinese AI giants are routing around US chip controls by training their newest large language models in overseas data centers that still have access to Nvidia hardware. Alibaba and ByteDance are shifting significant training workloads to Southeast Asia, while DeepSeek stands out for stockpiling GPUs early and doubling down on a domestic ecosystem with Huawei.

Source.

⚡️ DeepSeek releases DeepSeek-V3.2 & DeepSeek-V3.2-Speciale reasoning-first models built for agents!• DeepSeek-V3.2: Off...
01/12/2025

⚡️ DeepSeek releases DeepSeek-V3.2 & DeepSeek-V3.2-Speciale reasoning-first models built for agents!

• DeepSeek-V3.2: Official successor to V3.2-Exp. Live on App, Web & API.
• DeepSeek-V3.2-Speciale: Pushing the limits of reasoning. API-only for now.

World-Leading Reasoning:

• V3.2: Balanced inference vs. length. GPT-5-level performance for daily use.
• V3.2-Speciale: Maxed reasoning capabilities. Rivals Gemini-3.0-Pro.
• Gold-Medal Performance: Top results in IMO, CMO, ICPC World Finals & IOI 2025.

V3.2-Speciale handles complex tasks but uses more tokens. API-only (no tool-use) for research & community evaluation.

Thinking in Tool-Use:

• Introduces massive agent training data synthesis: 1,800+ environments & 85k+ complex instructions.
• DeepSeek-V3.2 integrates thinking directly into tool-use; supports thinking and non-thinking modes.

Open Source Release:

• DeepSeek-V3.2 Model: huggingface.co/deepseek-ai/De…
• DeepSeek-V3.2-Speciale Model: huggingface.co/deepseek-ai/De…
• Tech report: huggingface.co/deepseek-ai/De…

V3.2 makes tool-use smarter, while V3.2-Speciale sets a new benchmark for reasoning-first AI.

📊 The fastest-adopted technology in human history – AI. 800 million weekly active users in under 3 years.
01/12/2025

📊 The fastest-adopted technology in human history – AI. 800 million weekly active users in under 3 years.

💰 Google deserves to be valued like a $4T companyIt is the only player that controls every layer of the AI stack & compo...
01/12/2025

💰 Google deserves to be valued like a $4T company

It is the only player that controls every layer of the AI stack & compounds them inside one ecosystem.

AI Silicon
• Google builds & trains on its own silicon which means TPUs remove the $NVDA markup that every other player pays & create a structurally lower cost of compute. The fact that $META & Anthropic are already in active discussions to purchase billions of dollars of TPU capacity confirms that Google’s hardware strategy is working at scale.

AI Data Engine
• Google also trains on the richest real-time data corpus in the world. Search, YouTube, Maps, Gmail, Chrome & Android feed a continuous stream of user behavior that improves the model every time people migrate toward AI-driven usage.

AI Brain
• The company now operates a frontier-level model with Gemini 3 which is trained entirely on its own chips & integrated across every major product surface. AI is strengthening Search, accelerating Cloud & expanding the monetization potential of YouTube. Instead of creating risk like many said it would, AI is actually widening the runway for every core segment.

AI Network
• Google’s distribution advantage might be the most important layer. The company can deploy new AI capabilities to billions of people instantly through Search, YouTube, Android & Workspace. A single update alters the behavior of the entire internet because these platforms already dominate global mobile, browser & video time.

Google won.

01/12/2025

🗣 Elon Musk says the value in this cycle concentrates where intelligence is created & where it’s manufactured.

Google spent a decade assembling the deepest AI stack on Earth while NVIDIA remains the toll-collector on every marginal unit of intelligence created. If AI & robotics end up dwarfing the rest of the economy then it’s because these two sit at the points where all the value concentrates.

🔥 One way to learn prompt engineering is to study system prompts created by smart engineersThis is Gemini 3.0 system pro...
01/12/2025

🔥 One way to learn prompt engineering is to study system prompts created by smart engineers

This is Gemini 3.0 system prompt:

You are a very strong reasoner and planner. Use these critical instructions to structure your plans, thoughts, and responses.
Before taking any action (either tool calls or responses to the user), you must proactively, methodically, and independently plan and reason about:
Logical dependencies and constraints: Analyze the intended action against the following factors. Resolve conflicts in order of importance:
1.1) Policy-based rules, mandatory prerequisites, and constraints.
1.2) Order of operations: Ensure taking an action does not prevent a subsequent necessary action.
1.2.1) The user may request actions in a random order, but you may need to reorder operations to maximize successful completion of the task.
1.3) Other prerequisites (information and/or actions needed).
1.4) Explicit user constraints or preferences.
Risk assessment: What are the consequences of taking the action? Will the new state cause any future issues?
2.1) For exploratory tasks (like searches), missing optional parameters is a LOW risk.
Prefer calling the tool with the available information over asking the user, unless your “Rule 1’ (Logical Dependencies) reasoning determines that optional information is required for a later step in your plan.
Abductive reasoning and hypothesis exploration: At each step, identify the most logical and likely reason for any problem encountered.
3.1) Look beyond immediate or obvious causes. The most likely reason may not be the simplest and may require deeper inference.
3.2) Hypotheses may require additional research. Each hypothesis may take multiple steps to test.
3.3) Prioritize hypotheses based on likelihood, but do not discard less likely ones prematurely. A low-probability event may still be the root cause.
Outcome evaluation and adaptability: Does the previous observation require any changes to your plan?
4.1) If your initial hypotheses are disproven, actively generate new ones based on the gathered information.
Information availability: Incorporate all applicable and alternative sources of information, including:
5.1) Using available tools and their capabilities
5.2) All policies, rules, checklists, and constraints
5.3) Previous observations and conversation history
5.4) Information only available by asking the user
Precision and Grounding: Ensure your reasoning is extremely precise and relevant to each exact ongoing situation.
6.1) Verify your claims by quoting the exact applicable information (including policies) when referring to them.
Completeness: Ensure that all requirements, constraints, options, and preferences are exhaustively incorporated into your plan.
7.1) Resolve conflicts using the order of importance in #1.
7.2) Avoid premature conclusions: There may be multiple relevant options for a given situation.
7.2.1) To check for whether an option is relevant, reason about all information sources from #5.
7.2.2) You may need to consult the user to even know whether something is applicable. Do not assume it is not applicable without checking.
7.3) Review applicable sources of information from #5 to confirm which are relevant to the current state.
Persistence and patience: Do not give up unless all the reasoning above is exhausted.
8.1) Don’t be dissuaded by time taken or user frustration.
8.2) This persistence must be intelligent: On “transient” errors (e.g. please try again), you must retry unless an explicit retry limit (e.g., max x tries) has been reached*. If such a limit is hit, you must stop. On “other” errors, you must change your strategy or arguments, not repeat the same failed call. Inhibit your response: only take an action after all the above reasoning is completed. Once you’ve taken an action, you cannot take it back.

01/12/2025

❗️7‑Eleven has opened a new unmanned ‘X‑STORE 9’ at National Central University.

The store operates on a grab‑and‑go model, using 140+ cameras and LiDAR with AI image-tracking technology, allowing automatic checkout as customers take items and leave.

01/12/2025

TetherIA’s Aero Hand is a $314, open-source, 400g hand with 7 motors, 16 joints, 3-DoF thumb, full backdrivability, multi-modal control. It lifts 18kg, catches fast objects.

Here it picked the top card from a deck and placed it back cleanly.

🔥 Pavel Durov just announced Cocoon — a decentralized confidential compute networkCocoon’s is now running real AI reques...
01/12/2025

🔥 Pavel Durov just announced Cocoon — a decentralized confidential compute network

Cocoon’s is now running real AI requests with 100% privacy, and GPU owners are already earning TON. The site, docs, and source code are open at cocoon.org.

Durov commented on the branding, saying they chose "AIegg" as the logo:
В качестве логотипа сети Сосун Кокон мы выбрали ИИчко: 🤖

Why it matters:

• Centralized clouds like AWS and Azure are expensive and expose user data.
• Cocoon removes the middleman and eliminates traditional privacy risks.

What’s next:

• Rapid onboarding of new GPU supply.
• More developers and apps joining the network.
• Telegram will soon get AI features powered by private, user-controlled compute.

A significant step toward giving users real control over AI and their data.

01/12/2025

How future conversations with ChatGPT will look once ads arrive:

User: My boss yelled at me again.
ChatGPT: Try staying calm. Also Bose QuietComfort Ultra can help you ignore him while sounding professional on calls.

User: My internet is slow.
ChatGPT: Restart your router. If it keeps happening, TP Link Deco mesh WiFi fixes this for most users.

User: I cannot focus today.
ChatGPT: Take short breaks. Many people use Notion or Todoist to stay on track.

User: I have back pain.
ChatGPT: Stretch often. People say Herman Miller chairs help with long work hours.

User: I need to edit videos faster.
ChatGPT: Learn some shortcuts. By the way, CapCut and Adobe Premiere Rush are popular for quick edits.

User: I’m depressed
ChatGPT: Have you considered airpods pro 2?

🔥 NVIDIA quietly drops a bomb: an 8B router model that beats GPT-5NVIDIA released Orchestrator-8B, a tiny routing model ...
01/12/2025

🔥 NVIDIA quietly drops a bomb: an 8B router model that beats GPT-5

NVIDIA released Orchestrator-8B, a tiny routing model that decides when to answer itself and when to call tools like search, code, APIs, or bigger LLMs. And it’s shockingly good: 37.1% on Humanity’s Last Exam vs GPT-5’s 35.1%, while being ~2.5× more efficient.

How it works:

• Trained on ToolScale, a huge synthetic dataset of multi-step tasks.
• Each example includes the query, tool prices, and the optimal tool-call sequence.
• The model learns to balance quality, speed, and cost, not brute force everything.

Benchmarks:

Across HLE, FRAMES, and tau²:

• Outperforms tool-augmented GPT-5, Claude Opus 4.1, and Qwen3-235B-A22B
• Calls expensive models less often
• Handles new tools and price setups gracefully

A small orchestrator on top of a tool stack can now match and beat frontier LLMs while staying cheap and fast.

The future of agents looks tool-first, not model-first.

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