Last week on December 6th, Google unveiled Gemini, its most ambitious and capable AI model to date. Gemini marks a significant leap forward in generative AI, offering exceptional capabilities and promising to redefine how we interact with technology.
Here’s what to know
- Multimodal learning: Unlike previous AI models primarily trained on text, Gemini can process and understand text, images, audio, and more simultaneously. This allows for more nuanced comprehension and a wider range of applications.
- Enhanced code generation: Gemini integrates AlphaCode 2, a code-generating system surpassing 85% of coding competition participants. This opens up exciting possibilities for automated programming and software development.
- Advanced natural language processing: Gemini excels in understanding natural language, generating human-quality text, and engaging in complex conversations.
- Multimodal creativity: Gemini can create diverse content formats, including poems, code, scripts, music, and images, all in the same session. This opens up a new way to interact with information under the Google ecosystem.
While Gemini is still under development its capabilities are already impressive. It represents the first step in a continuous learning and development process for Google.
It’s also a significant milestone in generative AI, with its ability to process and understand diverse information modalities. This allows for deeper comprehension and communication giving realtime responses along the way.
If you’re looking for an insight into how this will change the core search experience, check this video for a glimpse into the near future. 🔗
Around the web
v0.dev Is Pure Magic
The new AI startup v0 🔗 is taking the “Make it real” trend to another level. In Private beta and with a full integration into Vercel, take any screenshot and create it into a fully working prototype deployed in minutes.
🗣️ Thought of the week
What if your next project was simpler than anyone expected but still innovative, taking an idea previously impossible without AI and transforming it completely?
The more I work with AI the more realistic the unrealistic seems. I’ve shifted my thinking from first-to-market never-before-seen ideas to “how can AI take something no one would have dared to do before – and do it”.
Ever wonder what Large Language Models look like when you dive deep below the surface of a chat interface? This visualization 🔗, while incredibly technical, gives a great understanding of the shear complexity that make up LLMs.
It overviews basic, and then more complex versions, and makes you wonder just how much more elaborate GPT-4 and newer age models ‘look’ when compared to GPT 3 (the largest visual) here!