The first model from this latest generation is an experimental version of Gemini 2.5 Pro, which DeepMind says has achieved state-of-the-art results across a wide range of benchmarks.

According to Koray Kavukcuoglu, CTO of Google DeepMind, the Gemini 2.5 models are “thinking models”.  This signifies their capability to reason through their thoughts before generating a response, leading to enhanced performance and improved accuracy.    

The capacity for “reasoning” extends beyond mere classification and prediction, Kavukcuoglu explains. It encompasses the system’s ability to analyse information, deduce logical conclusions, incorporate context and nuance, and ultimately, make informed decisions.

DeepMind has been exploring methods to enhance AI’s intelligence and reasoning capabilities for some time, employing techniques such as reinforcement learning and chain-of-thought prompting. This groundwork led to the recent introduction of their first thinking model, Gemini 2.0 Flash Thinking.    

“Now, with Gemini 2.5,” says Kavukcuoglu, “we’ve achieved a new level of performance by combining a significantly enhanced base model with improved post-training.”

Google plans to integrate these thinking capabilities directly into all of its future models—enabling them to tackle more complex problems and support more capable, context-aware agents.    

Gemini 2.5 Pro secures the LMArena leaderboard top spot

Gemini 2.5 Pro Experimental is positioned as DeepMind’s most advanced model for handling intricate tasks. As of writing, it has secured the top spot on the LMArena leaderboard – a key metric for assessing human preferences – by a significant margin, demonstrating a highly capable model with a high-quality style:

Gemini 2.5 is a ‘pro’ at maths, science, coding, and reasoning

Gemini 2.5 Pro has demonstrated state-of-the-art performance across various benchmarks that demand advanced reasoning.

Notably, it leads in maths and science benchmarks – such as GPQA and AIME 2025 – without relying on test-time techniques that increase costs, like majority voting. It also achieved a state-of-the-art score of 18.8% on Humanity’s Last Exam, a dataset designed by subject matter experts to evaluate the human frontier of knowledge and reasoning.

DeepMind has placed significant emphasis on coding performance, and Gemini 2.5 represents a substantial leap forward compared to its predecessor, 2.0, with further improvements in the pipeline. 2.5 Pro excels in creating visually compelling web applications and agentic code applications, as well as code transformation and editing.

On SWE-Bench Verified, the industry standard for agentic code evaluations, Gemini 2.5 Pro achieved a score of 63.8% using a custom agent setup. The model’s reasoning capabilities also enable it to create a video game by generating executable code from a single-line prompt.

Building on its predecessors’ strengths

Gemini 2.5 builds upon the core strengths of earlier Gemini models, including native multimodality and a long context window. 2.5 Pro launches with a one million token context window, with plans to expand this to two million tokens soon. This enables the model to comprehend vast datasets and handle complex problems from diverse information sources, spanning text, audio, images, video, and even entire code repositories.    

Developers and enterprises can now begin experimenting with Gemini 2.5 Pro in Google AI Studio. Gemini Advanced users can also access it via the model dropdown on desktop and mobile platforms. The model will be rolled out on Vertex AI in the coming weeks.    

Google DeepMind encourages users to provide feedback, which will be used to further enhance Gemini’s capabilities.

(Photo by Anshita Nair)

See also: DeepSeek V3-0324 tops non-reasoning AI models in open-source first

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 other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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

The post Gemini 2.5: Google cooks up its ‘most intelligent’ AI model to date appeared first on AI News.

A year after introducing the Gemini 1.0 model, this major upgrade incorporates enhanced multimodal capabilities, agentic functionality, and innovative user tools designed to push boundaries in AI-driven technology.

Leap towards transformational AI  

Reflecting on Google’s 26-year mission to organise and make the world’s information accessible, Pichai remarked, “If Gemini 1.0 was about organising and understanding information, Gemini 2.0 is about making it much more useful.”

Gemini 1.0, released in December 2022, was notable for being Google’s first natively multimodal AI model. The first iteration excelled at understanding and processing text, video, images, audio, and code. Its enhanced 1.5 version became widely embraced by developers for its long-context understanding, enabling applications such as the productivity-focused NotebookLM.

Now, with Gemini 2.0, Google aims to accelerate the role of AI as a universal assistant capable of native image and audio generation, better reasoning and planning, and real-world decision-making capabilities. In Pichai’s words, the development represents the dawn of an “agentic era.”

“We have been investing in developing more agentic models, meaning they can understand more about the world around you, think multiple steps ahead, and take action on your behalf, with your supervision,” Pichai explained.

Gemini 2.0: Core features and availability

At the heart of today’s announcement is the experimental release of Gemini 2.0 Flash, the flagship model of Gemini’s second generation. It builds upon the foundations laid by its predecessors while delivering faster response times and advanced performance.

Gemini 2.0 Flash supports multimodal inputs and outputs, including the ability to generate native images in conjunction with text and produce steerable text-to-speech multilingual audio. Additionally, users can benefit from native tool integration such as Google Search and even third-party user-defined functions.

Developers and businesses will gain access to Gemini 2.0 Flash via the Gemini API in Google AI Studio and Vertex AI, while larger model sizes are scheduled for broader release in January 2024.

For global accessibility, the Gemini app now features a chat-optimised version of the 2.0 Flash experimental model. Early adopters can experience this updated assistant on desktop and mobile, with a mobile app rollout imminent.

Products such as Google Search are also being enhanced with Gemini 2.0, unlocking the ability to handle complex queries like advanced math problems, coding enquiries, and multimodal questions.

Comprehensive suite of AI innovations  

The launch of Gemini 2.0 comes with compelling new tools that showcase its capabilities.

One such feature, Deep Research, functions as an AI research assistant, simplifying the process of investigating complex topics by compiling information into comprehensive reports. Another upgrade enhances Search with Gemini-enabled AI Overviews that tackle intricate, multi-step user queries.

The model was trained using Google’s sixth-generation Tensor Processing Units (TPUs), known as Trillium, which Pichai notes “powered 100% of Gemini 2.0 training and inference.”

Trillium is now available for external developers, allowing them to benefit from the same infrastructure that supports Google’s own advancements.

Pioneering agentic experiences  

Accompanying Gemini 2.0 are experimental “agentic” prototypes built to explore the future of human-AI collaboration, including:

• Project Astra: A universal AI assistant

First introduced at I/O earlier this year, Project Astra taps into Gemini 2.0’s multimodal understanding to improve real-world AI interactions. Trusted testers have trialled the assistant on Android, offering feedback that has helped refine its multilingual dialogue, memory retention, and integration with Google tools like Search, Lens, and Maps. Astra has also demonstrated near-human conversational latency, with further research underway for its application in wearable technology, such as prototype AI glasses.

• Project Mariner: Redefining web automation 

Project Mariner is an experimental web-browsing assistant that uses Gemini 2.0’s ability to reason across text, images, and interactive elements like forms within a browser. In initial tests, it achieved an 83.5% success rate on the WebVoyager benchmark for completing end-to-end web tasks. Early testers using a Chrome extension are helping to refine Mariner’s capabilities while Google evaluates safety measures that ensure the technology remains user-friendly and secure.

• Jules: A coding agent for developers  

Jules, an AI-powered assistant built for developers, integrates directly into GitHub workflows to address coding challenges. It can autonomously propose solutions, generate plans, and execute code-based tasks—all under human supervision. This experimental endeavour is part of Google’s long-term goal to create versatile AI agents across various domains.

• Gaming applications and beyond  

Extending Gemini 2.0’s reach into virtual environments, Google DeepMind is working with gaming partners like Supercell on intelligent game agents. These experimental AI companions can interpret game actions in real-time, suggest strategies, and even access broader knowledge via Search. Research is also being conducted into how Gemini 2.0’s spatial reasoning could support robotics, opening doors for physical-world applications in the future.

Addressing responsibility in AI development

As AI capabilities expand, Google emphasises the importance of prioritising safety and ethical considerations.

Google claims Gemini 2.0 underwent extensive risk assessments, bolstered by the Responsibility and Safety Committee’s oversight to mitigate potential risks. Additionally, its embedded reasoning abilities allow for advanced “red-teaming,” enabling developers to evaluate security scenarios and optimise safety measures at scale.

Google is also exploring safeguards to address user privacy, prevent misuse, and ensure AI agents remain reliable. For instance, Project Mariner is designed to prioritise user instructions while resisting malicious prompt injections, preventing threats like phishing or fraudulent transactions. Meanwhile, privacy controls in Project Astra make it easy for users to manage session data and deletion preferences.

Pichai reaffirmed the company’s commitment to responsible development, stating, “We firmly believe that the only way to build AI is to be responsible from the start.”

With the Gemini 2.0 Flash release, Google is edging closer to its vision of building a universal assistant capable of transforming interactions across domains.

See also: Machine unlearning: Researchers make AI models ‘forget’ data

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 other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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

The post Gemini 2.0: Google ushers in the agentic AI era  appeared first on AI News.

The restructuring sees the Gemini app team, led by Sissie Hsiao, joining Google DeepMind under the leadership of Demis Hassabis.

“Bringing the teams closer together will improve feedback loops, enable fast deployment of our new models in the Gemini app, make our post-training work proceed more efficiently and build on our great product momentum,” Pichai explained.

Additionally, the Assistant teams focusing on devices and home experiences will be integrated into the Platforms & Devices division. This reorganisation aims to align these teams more closely with the product surfaces they are developing for and consolidate AI smart home initiatives at Google under one umbrella.

Prabhakar Raghavan, a 12-year Google veteran, will transition from his current role to become the Chief Technologist at Google. Pichai praised Raghavan’s contributions, highlighting his leadership across various divisions including Research, Workspace, Ads, and Knowledge & Information (K&I).

“Prabhakar’s leadership journey at Google has been remarkable,” Pichai noted. “He led the Gmail team in launching Smart Reply and Smart Compose as early examples of using AI to improve products, and took Gmail and Drive past one billion users.”

Taking the helm of the K&I division will be Nick Fox, a long-standing Googler and member of Raghavan’s leadership team. Fox’s appointment as SVP of K&I comes on the back of his extensive experience across various facets of the company, including Product and Design in Search and Assistant, as well as Shopping, Travel, and Payments products.

“Nick has been instrumental in shaping Google’s AI product roadmap and collaborating closely with Prabhakar and his leadership team on K&I’s strategy,” comments Pichai. “I frequently turn to Nick to tackle our most challenging product questions and he consistently delivers progress with tenacity, speed, and optimism.”

The restructuring comes amid a flurry of AI-driven innovations across Google’s product lineup. Recent developments include the viral success of NotebookLM with Audio Overviews, enhancements to information discovery in Search and Lens, the launch of a revamped Google Shopping platform tailored for the AI era, advancements like AlphaProteo that could revolutionise protein design, and updates to the Gemini family of models.

Pichai also highlighted a significant milestone in Google’s healthcare AI initiatives, revealing that their AI system for detecting diabetic retinopathy has conducted 600,000 screenings to date. The company plans to expand access to this technology across India and Thailand.

“AI moves faster than any technology before it. To keep increasing the pace of progress, we’ve been making shifts to simplify our structures along the way,” Pichai explained.

(Photo by Mitchell Luo)

See also: Telefónica’s Wayra backs AI answer engine Perplexity

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 other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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

The post Google announces restructuring to accelerate AI initiatives appeared first on AI News.

The company released the devices much earlier than usual, as Google typically presents new Pixel models in the autumn. However, compared to previous versions, the changes in the new models are revolutionary.

The new smartphones feature more advanced integrations of Google’s AI technology. For instance, one unique Pixel feature allows users to search for information and images within their screenshots, thanks to a more deeply integrated approach. Additionally, through the Gemini chatbot, some features of these smartphones are available as overlays from other apps.

At Alphabet’s Bay View campus in Mountain View, California, Rick Osterloh, the Senior Vice President of Devices and Services at Google, informed visitors that the company plans to focus on practical applications of AI. He spent time describing the “Gemini era” to the audience, which will commence with the creation of Google’s advanced AI model.

The Pixel 9 series offers several models. The base model, the Pixel 9, features a 6.3-inch screen and costs $799. A larger alternative, the Pixel 9 Pro XL, has a 6.8-inch screen. A slightly enhanced version, the Pixel 9 Pro, offers a better camera system, though its price is higher. The final option is the foldable Pixel 9 Pro Fold.

Regarding the initial shipping date, Google stated at the event that the Pixel 9 and Pixel 9 Pro XL would ship in late August. The Pro and Pro Fold models will ship in September, with all models available for preorder starting August 13. During Google’s presentations at the event, Gemini’s new functions were showcased in a live demo, focusing on the latest conversation features. Additionally, the company announced updates to the product’s exterior design, the installation of Google’s advanced camera system, and the integration of the new Tensor G4 chip.

In addition to smartphones, the company unveiled new versions of the Pixel Watch 3 smartwatch and Pixel Buds Pro 2 wireless earbuds. The watch can track the user’s heart rate; if it stops, it will call emergency services. This feature will be available in the UK and the EU.

As reported by IDC, Google’s share in the global smartphone market was less than 1% in the second quarter of 2024. Samsung and Apple took the first and second places, with market shares of 18.9%, and 15.8%, respectively. In the US, Google ranks fourth among smartphone operating systems, holding 4.5% of the market share.

Industry analysts note that although Google Pixel is not among the best-selling smartphones, it showcases some of the benefits of the Android operating system. Android has become the dominant operating system, used by more than 80% of smartphone users worldwide. Consequently, many people, even those who have never used a Google Pixel, may indirectly experience and appreciate the features that Google products offer.

The event also touched upon Google’s further intentions and previous efforts to implement AI across its product lineup to stay at the top of the game. Not long ago, the company integrated AI improvements into its core products, including its search engine. Additionally, Google announced a content-sharing agreement it reached with Peloton. As a result, Fitbit Premium subscribers will have free access to the Peloton training class library.

(Image Credit: Google)

See also: Google’s Gemini 1.5 Pro dethrones GPT-4o

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 other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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

The post Google advances mobile AI in Pixel 9 smartphones appeared first on AI News.

For the past year, OpenAI’s GPT-4o and Anthropic’s Claude-3 have dominated the landscape. However, the latest version of Gemini 1.5 Pro appears to have taken the lead.

One of the most widely recognised benchmarks in the AI community is the LMSYS Chatbot Arena, which evaluates models on various tasks and assigns an overall competency score. On this leaderboard, GPT-4o achieved a score of 1,286, while Claude-3 secured a commendable 1,271. A previous iteration of Gemini 1.5 Pro had scored 1,261.

The experimental version of Gemini 1.5 Pro (designated as Gemini 1.5 Pro 0801) surpassed its closest rivals with an impressive score of 1,300. This significant improvement suggests that Google’s latest model may possess greater overall capabilities than its competitors.

It’s worth noting that while benchmarks provide valuable insights into an AI model’s performance, they may not always accurately represent the full spectrum of its abilities or limitations in real-world applications.

Despite Gemini 1.5 Pro’s current availability, the fact that it’s labelled as an early release or in a testing phase suggests that Google may still make adjustments or even withdraw the model for safety or alignment reasons.

This development marks a significant milestone in the ongoing race for AI supremacy among tech giants. Google’s ability to surpass OpenAI and Anthropic in benchmark scores demonstrates the rapid pace of innovation in the field and the intense competition driving these advancements.

As the AI landscape continues to evolve, it will be interesting to see how OpenAI and Anthropic respond to this challenge from Google. Will they be able to reclaim their positions at the top of the leaderboard, or has Google established a new standard for generative AI performance?

(Photo by Yuliya Strizhkina)

See also: Meta’s AI strategy: Building for tomorrow, not immediate profits

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 other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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

The post Google’s Gemini 1.5 Pro dethrones GPT-4o appeared first on AI News.

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

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 other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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

The post Google ushers in the “Gemini era” with AI advancements appeared first on AI News.

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

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 other leading events including BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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

The post Google pledges to fix Gemini’s inaccurate and biased image generation appeared first on AI News.

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’

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 other leading events including BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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

The post Google launches Gemini 1.5 with ‘experimental’ 1M token context appeared first on AI News.

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

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 Digital Transformation Week and Cyber Security & Cloud Expo.

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

The post Google launches Gemini to replace Bard chatbot appeared first on AI News.

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.

The post Google’s next-gen AI model Gemini outperforms GPT-4 appeared first on AI News.