Latest news with #GPT-4omini
The Sun
a day ago
- Business
- The Sun
AI needs to be smaller, reduce energy footprint: study
PARIS: The potential of artificial intelligence is immense -- but its equally vast energy consumption needs curbing, with asking shorter questions one way to achieve, said a UNESCO study unveiled Tuesday. A combination of shorter queries and using more specific models and could cut AI energy consumption by up to 90 percent without sacrificing performance, said UNESCO in a report published to mark the AI for Good global summit in Geneva. OpenAI CEO Sam Altman recently revealed that each request sent to its popular generative AI app ChatGPT consumes on average 0.34 Wh of electricity, which is between 10 and 70 times a Google search. With ChatGPT receiving around a billion requests per day that amounts to 310 GWh annually, equivalent to the annual electricity consumption of three million people in Ethiopia, for example, Moreover, UNESCO calculated that AI energy demand is doubling every 100 days as generative AI tools become embedded in everyday life. 'The exponential growth in computational power needed to run these models is placing increasing strain on global energy systems, water resources, and critical minerals, raising concerns about environmental sustainability, equitable access, and competition over limited resources,' the UNESCO report warned. However, it was able to achieve a nearly 90 percent reduction in electricity usage by reducing the length of its query, or prompt, as well as by using a smaller AI, without a drop in performance. Many AI models like ChatGPT are general-purpose models designed to respond on a wide variety of topics, meaning that it must sift through an immense volume of information to formulate and evaluate responses. The use of smaller, specialised AI models offers major reductions in electricity needed to produce a response. So did cutting the cutting prompts from 300 to 150 words. Being already aware of the energy issue, tech giants all now offer miniature versions with fewer parameters of their respective large language models. For example, Google sells Gemma, Microsoft has Phi-3, and OpenAI has GPT-4o mini. French AI companies have done likewise, for instance, Mistral AI has introduced its model Ministral. – AFP
Time of India
a day ago
- Business
- Time of India
AI needs to be smaller, reduce energy footprint: Study
Academy Empower your mind, elevate your skills The potential of artificial intelligence is immense -- but its equally vast energy consumption needs curbing, with asking shorter questions one way to achieve, said a UNESCO study unveiled Tuesday.A combination of shorter queries and using more specific models and could cut AI energy consumption by up to 90% without sacrificing performance, said UNESCO in a report published to mark the AI for Good global summit in CEO Sam Altman recently revealed that each request sent to its popular generative AI app ChatGPT consumes on average 0.34 Wh of electricity, which is between 10 and 70 times a Google ChatGPT receiving around a billion requests per day that amounts to 310 GWh annually, equivalent to the annual electricity consumption of three million people in Ethiopia, for UNESCO calculated that AI energy demand is doubling every 100 days as generative AI tools become embedded in everyday life."The exponential growth in computational power needed to run these models is placing increasing strain on global energy systems, water resources, and critical minerals, raising concerns about environmental sustainability, equitable access, and competition over limited resources," the UNESCO report it was able to achieve a nearly 90 percent reduction in electricity usage by reducing the length of its query, or prompt, as well as by using a smaller AI, without a drop in AI models like ChatGPT are general-purpose models designed to respond on a wide variety of topics, meaning that it must sift through an immense volume of information to formulate and evaluate use of smaller, specialised AI models offers major reductions in electricity needed to produce a did cutting the cutting prompts from 300 to 150 already aware of the energy issue, tech giants all now offer miniature versions with fewer parameters of their respective large language example, Google sells Gemma, Microsoft has Phi-3, and OpenAI has GPT-4o mini. French AI companies have done likewise, for instance, Mistral AI has introduced its model Ministral.
Yahoo
06-03-2025
- Business
- Yahoo
Unlike Google Search, privacy-focused DuckDuckGo takes it slow with AI
Undoubtedly, AI will significantly impact areas like search in the coming years. However, the speed at which this integration should occur is debatable. Industry leader Google is fully committed to incorporating AI into all its search tools, while privacy-focused DuckDuckGo allows users to decide how far into AI they want to go. This flexibility could score DuckDuckGO major points in a world where not everyone is prepared to embrace AI — at least not yet fully. According to a recent report by The Verge, DuckDuckGo has ambitious plans to incorporate AI into its popular search engine. As a result, users will soon see AI-generated answers for specific queries on the DuckDuckGo website and the app. Additionally, the company is integrating web search capabilities within its AI chatbot. Both of these tools are now exiting their beta phase. DuckDuckGo introduced its AI-assisted answers, known as DuckAssist, in 2023. The company initially emphasized that this tool aims to be a 'less obnoxious' alternative to features like Google's AI Overviews. The result is a service that provides more concise responses while allowing users to control how often they see AI-generated results. Even more impressively, DuckDuckGo offers the option to disable these responses altogether. In the current version of the DuckDuckGo app, you can choose to use Assist, Sometimes, On-demand, Often, or Never. Sometimes only shows AI-assisted answers when highly relevant, while On-demand only shows AI-assisted answers if you click the Assist button. When set to the Often setting, AI-assisted answers frequently appear on a broader range of searches. Just how frequently? Gabriel Weinberg, the CEO and founder of DuckDuckGo, says only 20% of searches are currently AI-generated, although that is expected to rise over time. They explain: 'We'd like to raise that over time … That's another major area that we're working on … We want to kind of stay conservative with it. We don't want to put it in front of people if we don't think it's right.' Even while implementing AI, DuckDuckGo hasn't forgotten its privacy roots. Interactions with AI models are done anonymously every time by hiding your IP address, regardless of the model you choose. DuckDuckGo's agreements with the AI company behind each available model also guarantee that your data isn't used for training. Currently, you can toggle between GPT-4o mini, o3-mini, Llama 3.3, Mistral Small 3, and Claude 3 Haiku. DuckDuckGo's AI tools can be explored via its chatbot on the website or through the DuckDuckGo browser. Additionally, AI-assisted answers will appear in the DuckDuckGo search engine. If you're using Google Search, the most popular search tool in the world, it's essential to understand that entirely opting out of all of Google's AI search features isn't straightforward. However, there are ways to minimize or bypass the AI Overviews feature. For instance, many of these features are still considered experimental, making it somewhat easier to disable them. Additionally, third parties have discovered workarounds, although many of these are hit-or-miss. Ultimately, it's important to recognize that Google's AI Overviews are becoming integral to the overall Google Search experience, for better or worse. Many people will be pleased to know that DuckDuckGo is taking AI seriously and integrating it into its various search products. However, the company recognizes that not everyone wants to use AI. Opting out of AI features is a simple process for those users. That option is also available for those who wish to experience AI search in small doses.
Yahoo
27-02-2025
- Business
- Yahoo
Inventor of Diffusion Technology Underlying Sora and Midjourney Launches Inception to Bring Advanced Reasoning AI Everywhere, from Wearables to Data Centers
Breakthrough reduces AI computational costs by 90%, enabling widespread deployment of advanced reasoning AI from the cloud to personal devices. Built by top AI researchers from Stanford, UCLA, and Cornell who developed foundational ML technologies including the algorithms that power Midjourney and Sora. PALO ALTO, Calif., February 26, 2025--(BUSINESS WIRE)--Inception today introduced the first-ever commercial-scale diffusion-based large language models (dLLMs), a new approach to AI that significantly improves models' speed, efficiency, and capabilities. Stemming from research at Stanford, Inception's dLLMs achieve up to 10x faster inference speeds and 10x lower inference costs while unlocking advanced capabilities in reasoning, controllable generation, and multi-modal data analysis. Inception's technology enables enterprises to deploy intelligent agents and real-time decision-making systems at scale, setting a new standard for AI performance. Artificial Analysis, an independent AI measurement firm, has benchmarked Inception's dLLMs at speeds 10x faster than leading speed-optimized models like GPT-4o mini and Claude 3.5 Haiku. Indeed, Inception's models achieve speeds previously attainable only with specialized hardware. On Copilot Arena, an LLM performance leaderboard, developers rate Inception's model ahead of frontier closed-source models including GPT-4o. Unlike traditional models that generate text sequentially, Inception's diffusion-based approach—the same technology behind today's most advanced AI systems like Midjourney for images and OpenAI's Sora for video generation—simultaneously generates entire blocks of text. Think of it like watching an image gradually sharpen into detail rather than appearing one pixel at a time. This parallel processing enables faster, more efficient generation and more precise control over output quality. The efficiency of diffusion models opens up possibilities for advanced reasoning, which currently requires minutes of computational "thought." It can power agentic applications in fields ranging from code generation to customer support by enabling agents that can plan and iterate while maintaining a responsive user experience. Advanced reasoning models can now deliver answers on the spot, unlocking their full potential for developers and enterprises alike. Similarly, Inception's speed transforms code auto-complete tools, eliminating frustrating delays and making them seamless and intuitive. The efficiency of diffusion models means that they run quickly even on edge computing devices, bringing AI from data centers to consumer devices. "AI today is limited because the core algorithm underlying generation is very inefficient, which makes scaling the most powerful models to real-world applications challenging," says Inception CEO and Stanford Professor Stefano Ermon. "Just as Deepseek identified ways of reducing the costs of model training, we have developed approaches to make model inference vastly more efficient and accessible." dLLMs' benefits are not limited to speed and cost savings. Inception's roadmap includes launching models with several other technological advantages provided by diffusion modeling: dLLMs can provide advanced reasoning capabilities by leveraging their built-in error correction mechanisms to fix mistakes and hallucinations. dLLMs can provide a unified framework for processing multimodal data, making them more performant on multimodal tasks. dLLMs can deliver control over output structure, making them ideal for function calling and structured data generation. Inception was founded by professors from Stanford, UCLA, and Cornell—pioneers in diffusion modeling and cornerstone AI technologies, including flash attention, decision transformers, and direct preference optimization. The company's engineering team includes veterans from DeepMind, Microsoft, Meta, OpenAI, and NVIDIA. The company is recruiting researchers and engineers with experience in LLM optimization and deployment. Explore career opportunities at Inception's dLLMs are now available for hands-on exploration. Access Inception's first models at this playground. Also, sign up to get early access to upcoming model releases. For enterprises looking to integrate Inception's technology, its dLLMs are available via an API and through on-premise deployment. Fine-tuning support is provided. Contact the company at sales@ to explore partnership opportunities and bring the next generation of AI to your applications. Visit to get started. About Inception Inception is pioneering diffusion-based large language models (dLLMs) that enable faster, more efficient, and more capable AI systems for enterprise applications. View source version on Contacts Press Contact: VSC, on behalf of Inceptionnatalieb@ Sign in to access your portfolio
