Google has introduced three new experimental AI models, including an 8 billion parameter version of Gemini 1.5 Flash, along with updated versions of the 1.5 Pro and Flash. The primary aim is to gather developer feedback and ensure optimal functioning before a full rollout. Developers can easily specify the use of these experimental models via the API, which is a strategic move to prevent issues stemming from sudden model updates. This minimizes risk by allowing developers to identify potential failures in functionality early on. Notably, the Gemini 1.5 Flash model has made significant improvements in performance metrics, moving up from 23rd to 6th place in the Large Model Systems Organization leaderboard. However, some users have reported specific failure modes, reminiscent of past models, indicating the presence of 'lazy coding disease' where the model struggles to produce direct code outputs. This feedback is critical for Google as it continues fine-tuning the Gemini models to enhance reliability and user experience.
Our 181st episode with a summary and discussion of last week's big AI news!
With hosts Andrey Kurenkov and Jeremie Harris
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In this episode:
- Google's AI advancements with Gemini 1.5 models and AI-generated avatars, along with Samsung's lithography progress.
- Microsoft's Inflection usage caps for Pi, new AI inference services by Cerebrus Systems competing with Nvidia.
- Biases in AI, prompt leak attacks, and transparency in models and distributed training optimizations, including the 'distro' optimizer.
- AI regulation discussions including California’s SB1047, China's AI safety stance, and new export restrictions impacting Nvidia’s AI chips.
Timestamps + Links:
- (00:00:00) Intro / Banter
- (00:03:08)Response to listener comments / corrections
- Tools & Apps
- Applications & Business
- Projects & Open Source
- Research & Advancements
- Policy & Safety
- Synthetic Media & Art
- (02:14:06) Outro