Google's Gemini just made GPT-4 look like a baby’s toy?
TLDRIn the wake of Microsoft's triumph over Google in the 2023 AI war, Google has retaliated with the release of its groundbreaking Gemini model. This multimodal AI excels in understanding text, sound, images, and video, and has demonstrated remarkable capabilities such as real-time video analysis and generation of content in various languages. Gemini's various versions cater to different needs, with the Ultra model outperforming GPT-4 on nearly all benchmarks except the H Swag, which assesses common sense. Despite its impressive technical paper and training methods, Gemini's full potential, particularly with the Ultra model, will be unveiled next year after additional safety tests and reaching a high score on the hell woke Benchmark.
Takeaways
- 🚀 Google faced intense competition from Microsoft in the 'Great AI War of 2023', leading to a shift in public usage towards Bing.
- 🌟 The GPT-4 model from Microsoft captured the essence of the AI age, outperforming Google's previous models.
- 🔥 Google unveiled the Gemini model, a highly anticipated AI model that surpasses GPT-4 in numerous benchmarks.
- 📅 The announcement of Gemini was made on December 7th, 2023, during a significant event in the AI industry.
- 🌐 Gemini is a multimodal large language model, capable of processing text, sound, images, and video.
- 🎥 Google's demo showcased Gemini's ability to understand and respond to video content in real-time, including language recognition and logical tasks.
- 🖼️ Gemini can also generate images and music, demonstrating its versatility in multimodal outputs.
- 🔍 The AI is adept at logic and spatial reasoning, with potential applications in fields like civil engineering and architecture.
- 🔧 Google introduced Alpha Code 2, an AI that outperforms 90% of competitive programmers in solving complex abstract problems.
- 📈 In benchmarks, Gemini Pro often underperforms GPT-4, while Gemini Ultra outperforms both, except on the H Swag Benchmark where it lags behind.
- 🛠️ Gemini was trained using advanced tensor processing units and reinforcement learning to ensure high-quality outputs and avoid 'hallucinations'.
- 📆 The smaller and mid-range versions of Gemini will be available on Google Cloud on December 13th, with the Ultra version releasing next year after additional safety tests.
Q & A
What significant event is referred to as the 'great AI war of 2023'?
-The 'great AI war of 2023' refers to the intense competition between Google and Microsoft in the field of artificial intelligence, where Microsoft's GPT-4 captured the zeitgeist of the AI age and caused a shift in user preference from Google to Bing.
What is the key feature that differentiates Google's Gemini model from its predecessor, Lambda, and other models like GPT-4?
-Gemini is a multimodal large language model, meaning it's not only trained on text but also on sound, images, and video, allowing it to process and generate content across multiple mediums more effectively.
How did Google demonstrate the capabilities of Gemini during its presentation?
-Google demonstrated Gemini's capabilities by showcasing its ability to recognize and respond to a video feed in real-time, understand ongoing events in a video, play games like 'find the ball under the cup', and perform tasks like connecting the dots and generating images and music based on prompts.
What are the implications of Gemini's multimodal capabilities for different professions?
-The multimodal capabilities of Gemini suggest that various professionals, including civil engineers and software engineers, could leverage the AI for tasks like generating blueprints from land images or solving complex abstract problems, potentially making some traditional engineering roles obsolete.
How does Google's Alpha code 2 compare to human programmers?
-Alpha code 2 has been shown to perform better than 90% of competitive programmers, capable of solving highly complex abstract problems using techniques like dynamic programming, indicating a significant advancement in AI's ability to handle programming challenges.
What are the three different versions of Gemini, and what are their intended uses?
-The three versions of Gemini are Tall, Grande, and Ventti. Tall is designed for embedding on devices like Android phones, Grande is the general-purpose model, and Ventti, also referred to as Ultra, is the most powerful version designed for advanced AI applications that are mind-blowing to users.
What was the outcome of the comparison between Gemini Pro and GPT 4 Pro in terms of performance?
-While Gemini Pro underperforms GPT 4 in most situations, Gemini Ultra outperforms GPT 4 Pro on almost every benchmark, marking a significant leap in AI capabilities.
Why is Google's Gemini Ultra not available for public use yet?
-Gemini Ultra is not available until next year as it requires additional safety tests and must achieve a 100% score on the hell woke Benchmark before it can be released to ensure its reliability and ethical standards.
How did GPT 4 Pro react when asked about Gemini Ultra?
-When asked about Gemini Ultra, GPT 4 Pro started throwing shade at itself, indicating a level of concern or awareness of the superior capabilities of Gemini Ultra.
What training methodology did Google use for Gemini?
-Google trained Gemini using a version 5 tensor processing unit deployed in super PODS, each containing 4,096 chips. These PODS have dedicated optical switches for quick data transfer and can dynamically reconfigure into 3D torus topologies. The training data set included a vast array of internet content, filtered for quality and fine-tuned using reinforcement learning through human feedback.
What is the significance of Gemini Ultra's performance on the hell swag Benchmark?
-The hell swag Benchmark evaluates an AI's ability to understand common sense in natural language, which is crucial for a human-like interaction. Gemini Ultra underperforming on this benchmark is surprising and raises concerns about its ability to handle vague and ambiguous sentences effectively.
Outlines
🚀 Microsoft's AI Dominance and Google's Gemini Response
The paragraph discusses the AI war of 2023, where Microsoft's GPT-4 took the lead and caused Google to fall behind, leading to people using Bing. Google then unveiled its Gemini model, a multimodal large language model that surpasses GPT-4 in various benchmarks. Sundar's explanation of Gemini at google.io is highlighted, emphasizing its ability to handle text, sound, images, and video. The demo showcases Gemini's real-time recognition and response capabilities, its multilingual features, and its impressive logical and spatial reasoning. The paragraph also mentions Google's Alpha Code 2, which outperforms 90% of competitive programmers.
Mindmap
Keywords
💡AI War of 2023
💡Gemini Model
💡Multimodal
💡Benchmark
💡Tensor Processing Units
💡Reinforcement Learning
💡Hells Swag Benchmark
💡Aerodynamics
💡Alpha Code 2
💡The Bard Chatbot
💡Hell woke Benchmark
Highlights
Microsoft's blitzk attack in the great AI war of 2023 led to the capture of the Zeitgeist of the AI age by GPT 4.
Google's response to the AI war was the release of its highly anticipated Gemini model.
Gemini is a multimodal large language model, capable of understanding text, sound, images, and video.
Google demonstrated Gemini's ability to recognize and respond to a video feed in real time.
The AI can keep track of objects in an ongoing video feed, such as finding a ball under scrambled cups.
Gemini can perform connect the dots and generate images on the fly, like Sable diffusion.
The AI is capable of generating music based on a prompt, not just text to audio but also image to audio.
Gemini is adept at logic and spatial reasoning, such as determining which car will go faster based on aerodynamics.
Civil engineers will be able to use Gemini to generate blueprints for structures like bridges from a picture of land.
Alpha code 2 was unveiled by Google, outperforming 90% of competitive programmers in solving complex abstract problems.
Gemini comes in three sizes: Tall, Grande, and Ventti, with the Ultra version being the most powerful.
The Bard chatbot uses Gemini Pro, which has improved significantly since its introduction six months prior.
Gemini Pro underperforms GPT 4 in most situations, but Gemini Ultra outperforms it on almost every benchmark.
Gemini Ultra is the first model to outperform human experts on massive multitask language understanding.
Gemini Ultra underperforms GPT 4 on the H swag Benchmark, which evaluates common sense natural language understanding.
Google's training of Gemini involved a new version 5 tensor processing unit deployed in super PODS.
The training data set for Gemini includes everything found on the internet, filtered for quality and fine-tuned using reinforcement learning.
The Nano and Pro models of Gemini will be available on Google Cloud on December 13th, with the Ultra model releasing next year after additional safety tests.