Latest news with #Gemini2.0
Geeky Gadgets
29-05-2025
- Business
- Geeky Gadgets
Gemini TTS Native Audio Out : The Future of Human-Like Audio Content
What if your audiobook could whisper secrets, your podcast could laugh with its audience, or your virtual assistant could interrupt with perfect timing—just like a real conversation? With the advent of Gemini 2.5 Text-to-Speech (TTS), these possibilities are no longer confined to imagination. This new model by Google introduces native audio output that doesn't just replicate speech but redefines it, offering a level of expressiveness and realism that feels almost human. Whether you're a creator seeking to immerse your audience or a developer building lifelike interactions, Gemini 2.5 promises to transform how we think about audio content. Sam Witteveen explore the features that set Gemini 2.5 apart, from its customizable speech styles to its ability to simulate natural, multi-speaker conversations. You'll discover how this technology is reshaping industries like audiobook narration, AI-driven podcasts, and interactive dialogues, offering unprecedented levels of personalization and creative freedom. But it's not all smooth sailing—challenges like balancing expressiveness with naturalness and navigating multi-speaker setups remain. As we unpack its potential and limitations, consider how this innovation might inspire new ways to connect, create, and communicate through sound. Gemini 2.5 TTS Overview Key Features That Differentiate Gemini 2.5 Building on the foundation of its predecessor, Gemini 2.0, the 2.5 model incorporates several advanced features that elevate its speech generation capabilities. These features include: Customizable Speech Styles: Users can adjust tone, emotion, and delivery to suit specific contexts, such as whispering, laughter, or a more formal tone. Users can adjust tone, emotion, and delivery to suit specific contexts, such as whispering, laughter, or a more formal tone. Natural Interaction Simulation: The model supports realistic conversational elements, including interruptions and overlapping dialogue, making it ideal for storytelling or AI-driven podcasts. The model supports realistic conversational elements, including interruptions and overlapping dialogue, making it ideal for storytelling or AI-driven podcasts. Multi-Speaker Audio Generation: It enables the creation of dynamic, multi-voice content, with distinct personalities assigned to each speaker. These enhancements make Gemini 2.5 a powerful tool for applications that demand nuanced and expressive audio delivery. Its ability to simulate natural interactions and provide customizable speech styles sets it apart from other TTS models. Applications Across Industries Gemini 2.5 TTS is designed to cater to a broad spectrum of industries and use cases, offering practical solutions for creating high-quality audio content. Some of its most impactful applications include: Audiobook Narration: The model's expressive tones and emotional depth bring stories to life, enhancing listener engagement and immersion. The model's expressive tones and emotional depth bring stories to life, enhancing listener engagement and immersion. AI-Generated Podcasts: With its ability to produce multi-speaker content featuring natural conversational flow, Gemini 2.5 is well-suited for creating engaging podcasts. With its ability to produce multi-speaker content featuring natural conversational flow, Gemini 2.5 is well-suited for creating engaging podcasts. Interactive Dialogues: It supports the development of realistic dialogues for virtual assistants, training simulations, and creative projects. These use cases demonstrate the model's versatility and its potential to transform how audio content is produced, offering new levels of personalization and realism. Gemini TTS Advanced Text-to-Speech Model Watch this video on YouTube. Take a look at other insightful guides from our broad collection that might capture your interest in AI voice. Technical Capabilities and Accessibility Gemini 2.5 TTS is accessible through Google AI Studio, providing an intuitive platform for users to explore its features. Developers can also use the Gemini API for seamless integration, allowing programmatic customization of prompts, speech styles, and voice configurations. Key technical highlights include: Multi-Language Support: The model can generate speech in multiple languages, making it suitable for global applications and diverse audiences. The model can generate speech in multiple languages, making it suitable for global applications and diverse audiences. Voice Customization: Users can select from a variety of voice options to align with specific project requirements. Users can select from a variety of voice options to align with specific project requirements. Cloud-Based Infrastructure: Advanced processing capabilities are available through the cloud, making sure dynamic and efficient speech synthesis. While the model excels in expressiveness and versatility, some users may find multi-speaker setups challenging to configure effectively. Additionally, the expressive nature of the output may occasionally feel exaggerated, depending on the context. Comparison with Open source Alternatives Gemini 2.5 TTS competes with open source models like Kakoro, which offer advantages such as real-time processing and greater control over data through local deployment. These features make open source models appealing for privacy-conscious users or latency-sensitive applications. However, Gemini 2.5's cloud-based infrastructure enables more sophisticated features, such as dynamic speech synthesis and natural interaction simulation. The trade-offs include potential latency and reliance on cloud services, which may not suit all use cases. Nevertheless, for applications that prioritize advanced expressiveness and realism, Gemini 2.5 stands out as a compelling option. Opportunities and Challenges The preview of Gemini 2.5 TTS highlights its potential to redefine audio content creation. Its ability to generate expressive, multi-speaker audio opens up opportunities for innovative applications, including immersive storytelling, professional training tools, and AI-driven media production. However, certain challenges remain: Balancing Naturalness and Expressiveness: Some speech outputs may feel overly dramatic, requiring further refinement to achieve a more natural tone. Some speech outputs may feel overly dramatic, requiring further refinement to achieve a more natural tone. Complexity in Multi-Speaker Configurations: Setting up distinct voices for multi-speaker scenarios can be intricate and time-consuming. Setting up distinct voices for multi-speaker scenarios can be intricate and time-consuming. Unclear Pricing Structure: Limited information on costs and token usage may deter potential users from fully adopting the model. Despite these challenges, Gemini 2.5's innovative capabilities position it as a fantastic tool in the text-to-speech landscape. As the technology evolves, it promises to unlock new possibilities for creating engaging, personalized audio content. Media Credit: Sam Witteveen Filed Under: AI, Top News Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
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Business Standard
21-05-2025
- Business
- Business Standard
Google introduces 'AI Mode' for agentic web search experience: How it works
At the keynote session of Google I/O 2025, Google shared details on the evolution of its AI Mode, designed to deliver an agentic web search experience. Initially introduced in March, AI Mode has since been enhanced to offer users faster, more intuitive, and more comprehensive search results. Here are the new updates coming to the AI Mode: AI Mode: Automating complex search tasks Google said that the AI Mode represents a significant shift in how web searches are conducted. Instead of requiring users to sift through multiple pages of results, the tool autonomously handles the more tedious aspects of online research. For complex topics – where standard search methods may prove insufficient – AI Mode acts as a digital agent. It uses a technique called query fan-out, which dissects the user's primary query into smaller, more specific sub-queries. It then conducts multiple searches in parallel, collecting information from a wide range of sources. The system compiles this data into a single, in-depth response, complete with source links for verification. According to Google, this entire process is completed within seconds, significantly reducing the time and effort typically required to gather relevant and trustworthy information. AI Mode: Agentic web search rollout The rollout will initially kick off in the US and support tasks such as buying event tickets, making restaurant reservations, and booking local appointments. Google is partnering with platforms including Ticketmaster, StubHub, Resy, and Vagaro to deliver a seamless, integrated user experience. What Is Project Mariner Project Mariner is an experimental initiative built on Google's Gemini 2.0 AI model, aiming to redefine human-computer interaction within web browsers. According to Google, Project Mariner is designed to understand and interpret on-screen content, including text, images, code, and form elements. It enables the AI to interact meaningfully with websites by processing both visual and structural components, allowing it to complete complex tasks such as filling out forms, navigating UI elements, and compiling personalised search results.
Engadget
20-05-2025
- Business
- Engadget
AI Mode is now rolling out to everyone in the US
Google has begun rolling out AI Mode to every Search user in the US. The company announced the expansion during its I/O 2025 conference. Google first began previewing AI Mode with testers in its Labs program at the start of March. Since then, it has been gradually rolling out the feature to more people, including in recent weeks regular Search users. For the uninitiated, AI Mode is a chatbot built directly into Google Search. It lives in a separate tab, and was designed by the company to tackle more complicated queries than people have historically used its search engine to answer. For instance, you can use AI Mode to generate a comparison between different fitness trackers. Before today, the chatbot was powered by Gemini 2.0. Now it's running a custom version of Gemini 2.5. What's more, Google plans to bring many of AI Mode's capabilities to other parts of the Search experience. "AI Mode is where we'll first bring Gemini's frontier capabilities, and it's also a glimpse of what's to come," the company wrote in a blog post published during the event. "As we get feedback, we'll graduate many features and capabilities from AI Mode right into the core search experience in AI Overviews." Looking to the future, Google plans to bring Deep Research to AI Mode. Google was among the first companies to debut the tool back in December . Since then, most AI companies, including OpenAI , have gone on to offer their take on Deep Research, which you can use to prompt Gemini and other chatbots to take extra time to create a comprehensive report on a subject. With today's announcement, Google is making the tool available in a place where more of its users are likely to encounter it. Developing...
Tom's Guide
20-05-2025
- Business
- Tom's Guide
New to Google Gemini? Try these tips and prompts to get started
Ready to expand beyond ChatGPT? Adding Gemini to your AI toolbox can help you unlock new ways to boost creativity and workflows while tapping into an AI assistant that works within Google's own ecosystem. Many of Gemini's best models are available for free and each one serves a different purpose. Knowing how to make the most of each AI is you're a total beginner or just curious about what Gemini can do, these tips and prompts can help you get started, generate better results and discover what you've been from Google's official prompt engineering playbook, I'll break down actionable strategies to help you start smarter, refine outputs and discover why Gemini deserves a spot in your workflow. Let's dive in. Just because Gemini is Google's AI doesn't mean you should treat it like a Google search. In other words, you'll want to be as specific as possible with your prompts. You'll get the best results if you specify tone, format and purpose within each prompt. For example, if you need assistance writing an email, be sure to include the purpose of the email and whether it should be polite, professional or conversational. If you're using Gemini in Google Docs or Gmail, look for the preset options such as 'Help me write' and 'Help me visualize' in the side panel or compose window. These tools are designed to simplify and guide you as you is meant to be intuitive, so be sure to try each tool and explore what each one has to offer. You don't have to settle for the first answer after a prompt. You can ask the AI to 'make it funnier,' 'add stats' or 'reword this for clarity.' Gemini improves as you give it direction. You could also try prompt dusting by using a response you got from ChatGPT and getting clarity with Gemini. Get instant access to breaking news, the hottest reviews, great deals and helpful tips. You don't have to stick to Gemini 2.0. Unlike ChatGPT, Gemini offers a variety of models, many of which are free. Explore Gemini Live for help in real time, try NotebookLM for research and summarization, explore Veo for video generation, and try Gemini Deep Research to do a deep dive into just about any topic. In some areas, you can get a free trial of Gemini Advanced for one month to help you determine if the more premium features are for you. There are a multitude of differences, but there are some specific distinctions to note. While both are AI powerhouses, Gemini is tightly integrated with Google tools — like Gmail, Docs, and Search — so it may feel more seamless for users already in the Google ecosystem. It's also highly visual and useful for on-the-fly productivity within Android and Chrome devices. As mentioned, Gemini overs a variety of models that can be useful for different tasks. While some are similar to ChatGPT, such as Gemini Canvas, you may discover that you prefer one over the a variety of tools and crossing over in a hybrid scenario with ChatGPT and Gemini can also help you get the results you need. Gemini shines when you're stuck or need a fresh take. Try these prompts to spark ideas: Gemini can generate images right within the chat. To get started, be clear and descriptive so Gemini can get creative. Here are a few fun starter prompts: Image Tip: The more detail you give, the better. Mention color palettes, lighting, styles (like 'Pixar-style' or 'oil painting') and mood. If you are trying Gemini for the first time, you might notice some differences from other chatbots. However, it is fairly intuitive and the chat box is very similar. When in doubt, just ask Gemini! The AI assistant can help you work smarter and create faster. With the right prompts and a little practice, you may discover your new favorite chatbot, or at least one you'll want to add to your regular AI toolbox.
India Today
15-05-2025
- Business
- India Today
Google DeepMind brings AlphaEvolve, an AI tuned to tackle maths and computing problems
Ahead of the Google I/O 2025 annual developer conference, starting May 20, Google has announced its new AI agent called AlphaEvolve. The company introduces the AI agent as "an evolutionary coding agent powered by large language models for general-purpose algorithm discovery and optimisation." It explains that AlphaEvolve combines the inventive problem-solving strengths of Google's Gemini models with automated evaluators that validate solutions, employing an evolutionary system to refine and build on the most promising concepts. Let's delve deeper into Google's latest AI agent -- AlphaEvolve. advertisementGoogle DeepMind launches AlphaEvolveGoogle DeepMind has unveiled AlphaEvolve, a powerful new tool designed to tackle complex coding challenges by harnessing the strengths of its Gemini 2.0 large language models (LLMs). While LLMs are often hit-or-miss when it comes to generating code, AlphaEvolve takes a different approach. It continuously refines its output by scoring each of Gemini's suggestions, discarding weaker attempts and iteratively improving the stronger ones. This evolutionary process enables the system to produce highly optimised algorithms, many of which outperform the best human-written alternatives in terms of speed or standout example of AlphaEvolve's capabilities, as shared by the company, is its role in improving Google's job scheduling software, which allocates computing tasks across millions of servers worldwide. According to DeepMind, the refined algorithm has been running in production across Google's global data centres for over a year, unlocking a 0.7 per cent gain in computing efficiency—a modest-sounding figure, but a massive boost at Google's scale. advertisement AlphaEvolve on cutting down AI hallucinationsAlphaEvolve also addresses one of the major pitfalls of modern AI: hallucinations. Most AI systems, due to their probabilistic nature, sometimes fabricate confident but false answers. In fact, newer models, including OpenAI's o3, have demonstrated an increased tendency to do so. To combat this, AlphaEvolve introduces an automated evaluation layer. It prompts the model to generate multiple potential answers, then critiques and scores them based on accuracy, effectively filtering out unreliable DeepMind in its blogpost stated, "AlphaEvolve verifies, runs and scores the proposed programs using automated evaluation metrics. These metrics provide an objective, quantifiable assessment of each solution's accuracy and quality. This makes AlphaEvolve particularly helpful in a broad range of domains where progress can be clearly and systematically measured, like in math and computer science."How to use? Using AlphaEvolve involves presenting it with a clearly defined problem—this could include technical instructions, mathematical equations, code examples, or academic references. Crucially, the user must also supply a method for automatically assessing the output, typically via a formula or test mechanism. As such, AlphaEvolve is best suited to domains where self-verification is possible, like computing and systems the system is not without its limitations. AlphaEvolve can only tackle problems it can evaluate on its own, and it exclusively produces algorithmic solutions. This means it's less effective—or entirely unsuitable—for tackling open-ended, qualitative, or non-numerical problems.
