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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The controversy arose as users on social media platforms flooded feeds with examples of Gemini generating pictures depicting racially-diverse Nazis, black medieval English kings, and other improbable scenarios.

Google Gemini Image generation model receives criticism for being 'Woke'.

Gemini generated diverse images for historically specific prompts, sparking debates on accuracy versus inclusivity. pic.twitter.com/YKTt2YY265

— Darosham (@Darosham_) February 22, 2024

Meanwhile, critics also pointed out Gemini’s refusal to depict Caucasians, churches in San Francisco out of respect for indigenous sensitivities, and sensitive historical events like Tiananmen Square in 1989.

In response to the backlash, Jack Krawczyk, the product lead for Google’s Gemini Experiences, acknowledged the issue and pledged to rectify it. Krawczyk took to social media platform X to reassure users:

For now, Google says it is pausing the image generation of people:

While acknowledging the need to address diversity in AI-generated content, some argue that Google’s response has been an overcorrection.

Marc Andreessen, the co-founder of Netscape and a16z, recently created an “outrageously safe” parody AI model called Goody-2 LLM that refuses to answer questions deemed problematic. Andreessen warns of a broader trend towards censorship and bias in commercial AI systems, emphasising the potential consequences of such developments.

Addressing the broader implications, experts highlight the centralisation of AI models under a few major corporations and advocate for the development of open-source AI models to promote diversity and mitigate bias.

Yann LeCun, Meta’s chief AI scientist, has stressed the importance of fostering a diverse ecosystem of AI models akin to the need for a free and diverse press:

Bindu Reddy, CEO of Abacus.AI, has similar concerns about the concentration of power without a healthy ecosystem of open-source models:

As discussions around the ethical and practical implications of AI continue, the need for transparent and inclusive AI development frameworks becomes increasingly apparent.

(Photo by Matt Artz on Unsplash)

See also: Reddit is reportedly selling data for AI training

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The new capability allows Gemini 1.5 to process extremely long text passages – up to one million characters – to understand context and meaning. This dwarfs previous AI systems like Claude 2.1 and GPT-4 Turbo, which max out at 200,000 and 128,000 tokens respectively:

“Gemini 1.5 Pro achieves near-perfect recall on long-context retrieval tasks across modalities, improves the state-of-the-art in long-document QA, long-video QA and long-context ASR, and matches or surpasses Gemini 1.0 Ultra’s state-of-the-art performance across a broad set of benchmarks,” said Google researchers in a technical paper (PDF).

The efficiency of Google’s latest model is attributed to its innovative Mixture-of-Experts (MoE) architecture.

“While a traditional Transformer functions as one large neural network, MoE models are divided into smaller ‘expert’ neural networks,” explained Demis Hassabis, CEO of Google DeepMind.

“Depending on the type of input given, MoE models learn to selectively activate only the most relevant expert pathways in its neural network. This specialisation massively enhances the model’s efficiency.”

To demonstrate the power of the 1M token context window, Google showed how Gemini 1.5 could ingest the entire 326,914-token Apollo 11 flight transcript and then accurately answer specific questions about it. It also summarised key details from a 684,000-token silent film when prompted.

Google is initially providing developers and enterprises free access to a limited Gemini 1.5 preview with a one million token context window. A 128,000 token general release for the public will come later, along with pricing details.

For now, the one million token capability remains experimental. But if it lives up to its early promise, Gemini 1.5 could set a new standard for AI’s ability to understand complex, real-world text.

Developers interested in testing Gemini 1.5 Pro can sign up in AI Studio. Google says that enterprise customers can reach out to their Vertex AI account team.

(Image Credit: Google)

See also: Amazon trains 980M parameter LLM with ’emergent abilities’

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Unveiled in December, Bard was touted as a competitor to chatbots like ChatGPT but failed to impress in demos. Google staff even called the launch “botched” and slammed CEO Sundar Pichai.

Now rebranded as Gemini, Google says it represents the company’s “most capable family of models” for natural conversations. Two experiences are being launched: Gemini Advanced and a mobile app.

Gemini Advanced grants access to Ultra 1.0, billed by Google as its “largest and most capable state-of-the-art AI model.” In blind evaluations, third-party raters preferred Gemini Advanced with Ultra 1.0 over alternatives in complex tasks like coding, logical reasoning, and creative collaboration.  

The AI can serve as a tutor by creating personalised lessons and quizzes. Developers are aided for trickier coding problems. Gemini Advanced is designed to spark ideas and strategise ways that creators can grow their audiences.

Google plans to expand Gemini Advanced’s capabilities over time with exclusive features like expanded multimodal interactions, interactive coding, deeper data analysis, and more. The service already supports over 150 countries in English and will add more languages soon.  

Access to Gemini Advanced is granted through a new $19.99 (£18.99) per month Google One AI Premium Plan, including a free two-month trial. Subscribers get the latest Google AI advancements plus 2TB of storage from the existing Premium plan.  

Google claims Gemini Advanced underwent extensive trust and safety checks before its launch, including external reviews, to mitigate issues around unsafe content and bias. More details are available in an updated technical report (PDF).

Lastly, Google launched new mobile apps on Android and iOS to access basic Gemini features on-the-go. Users can ask for help with images, tasks, and more while out-and-about. Over time, the plan is for Gemini to become a true personal AI assistant.

The Gemini mobile apps are now available in the US as a dedicated app on Android and in the Google app on iOS, supporting English conversations initially. Next week, the apps expand to Japan and Korea, followed by more countries and languages thereafter.

(Image Credit: Google)

See also: DeepMind framework offers breakthrough in LLMs’ reasoning

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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

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