Gemini 1.5 Flash is a new addition to Google’s family of models, designed to be faster and more efficient to serve at scale. While lighter-weight than the 1.5 Pro, it retains the ability for multimodal reasoning across vast amounts of information and features the breakthrough long context window of one million tokens.

“1.5 Flash excels at summarisation, chat applications, image and video captioning, data extraction from long documents and tables, and more,” explained Demis Hassabis, CEO of Google DeepMind. “This is because it’s been trained by 1.5 Pro through a process called ‘distillation,’ where the most essential knowledge and skills from a larger model are transferred to a smaller, more efficient model.”

Meanwhile, Google has significantly improved the capabilities of its Gemini 1.5 Pro model, extending its context window to a groundbreaking two million tokens. Enhancements have been made to its code generation, logical reasoning, multi-turn conversation, and audio and image understanding capabilities.

The company has also integrated Gemini 1.5 Pro into Google products, including the Gemini Advanced and Workspace apps. Additionally, Gemini Nano now understands multimodal inputs, expanding beyond text-only to include images.

Google announced its next generation of open models, Gemma 2, designed for breakthrough performance and efficiency. The Gemma family is also expanding with PaliGemma, the company’s first vision-language model inspired by PaLI-3.

Finally, Google shared progress on Project Astra (advanced seeing and talking responsive agent), its vision for the future of AI assistants. The company has developed prototype agents that can process information faster, understand context better, and respond quickly in conversation.

“We’ve always wanted to build a universal agent that will be useful in everyday life. Project Astra, shows multimodal understanding and real-time conversational capabilities,” explained Google CEO Sundar Pichai.

“With technology like this, it’s easy to envision a future where people could have an expert AI assistant by their side, through a phone or glasses.”

Google says that some of these capabilities will be coming to its products later this year. Developers can find all of the Gemini-related announcements they need here.

See also: GPT-4o delivers human-like AI interaction with text, audio, and vision integration

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Demis Hassabis, CEO and Co-Founder of Google DeepMind, introduced Gemini as a multimodal model that is capable of seamlessly understanding and combining various types of information, including text, code, audio, image, and video.

Gemini comes in three optimised versions: Ultra, Pro, and Nano. The Ultra model boasts state-of-the-art performance, surpassing human experts in language understanding and demonstrating unprecedented capabilities in tasks ranging from coding to multimodal benchmarks.

What sets Gemini apart is its native multimodality, eliminating the need for stitching together separate components for different modalities. This groundbreaking approach, fine-tuned through large-scale collaborative efforts across Google teams, positions Gemini as a flexible and efficient model capable of running on data centres to mobile devices.

One of Gemini’s standout features is its sophisticated multimodal reasoning, enabling it to extract insights from vast datasets with remarkable precision. The model’s prowess extends to understanding and generating high-quality code in popular programming languages.

However, as Google ventures into this new era of AI, responsibility and safety remain paramount. Gemini undergoes rigorous safety evaluations, including assessments for bias and toxicity. Google is actively collaborating with external experts to address potential blind spots and ensure the model’s ethical deployment.

Gemini 1.0 is now rolling out across various Google products – including the Bard chatbot – with plans for integration into Search, Ads, Chrome, and Duet AI. However, the Bard upgrade will not be released in Europe pending clearance from regulators.

Developers and enterprise customers can access Gemini Pro via the Gemini API in Google AI Studio or Google Cloud Vertex AI. Android developers will also be able to build with Gemini Nano via AICore, a new system capability available in Android 14.

(Image Credit: Google)

See also: AI & Big Data Expo: AI’s impact on decision-making in marketing

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Cyber Security & Cloud Expo and Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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