The Unhackable Model

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THEWHITEBOX

TLDR;

This week, we discuss:

the sad reality of Google’s AI efforts {😋 Google Releases New Gemini 2.0 Models},

OpenAI’s latest potential moonshot {😟 OpenAI, The New Robotics and Consumer Hardware Company?},

how Apple continues to delve into AI research in very unorthodox ways {🤨 Apple’s Emotional Robots},

proof of AI’s deflationary powers, {🧑🏽‍🏫 CodeSignal’s Leadership Teaching Tool},

and a deep-dive on research by Anthropic that claims to have created the first unhackable AI model {TREND OF THE WEEK: Anthropic Presents the Unbreakable Model}

NEWSREEL

Google Release Gemini 2.0 Pro

Source

In a short blog post, Google announced the new releases of the Gemini 2.0 family of AI models, which aim to enhance performance, efficiency, and accessibility.

The updated Gemini 2.0 Flash model is now generally available through the Gemini API in Google AI Studio and Vertex AI. According to Google's own claims, this model offers developers improved performance for high-volume, high-frequency tasks.

Additionally, Google has released an experimental version of Gemini 2.0 Pro, designed to excel in coding tasks and handle complex prompts with a context window of 2 million tokens (i.e., you can send the model approximately up to 1.5 million words in every prompt). Additionally, although Google’s models are already the most cost-efficient (even more so than DeepSeek), the company is going the extra mile here, introducing Gemini 2.0 Flash-Lite, its most cost-effective model to date.

Gemini 2.0 Pro is already in the top two in the famous LMarena benchmark, making it the best LLM. It is only behind its thinking version (its reasoning version), Gemini 2.0 Exp Flash Thinking.

TheWhiteBox’s takeaway:

Google rules on paper, so why not in practice?

I’m shocked to see how little fuss Google’s releases make despite their models actively crushing it on benchmarks. Crucially, Google’s offering is extremely ‘Pareto optimized’ to the point that most frontier AI models in the Pareto curve (providing the best performance as a fraction of price) are Google’s, even ahead of the soul-crushing release of DeepSeek’s models (check above image).

Yes, DeepSeek doesn’t offer the best value for your money in AI, which just goes to prove how stupid NVIDIA’s crash was.

But why do the markets or space ignore Google?

I like to say that Google is the AMD of AI software. They have great AI models, which is the hardest part, but extremely shitty developer experiences; no one wants to get near Google’s products (especially Vertex AI) because their developer platforms are borderline unusable.

The analogy comes from the fact that AMD has top hardware but terrible developer stack and drivers when compared to NVIDIA’s CUDA platform.

I’ll say it as many times as I need: Google’s biggest rival is itself. They have the necessary cash, a top-tier AI lab, distribution, more compute than anyone else, and they are sitting on top of the biggest source of video data in the world: YouTube.

They literally have everything it takes to win.

And despite all that, and that their models are…

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