Latest news with #hybridreasoning
Forbes
15-07-2025
- Business
- Forbes
South Korea's LG Launches ‘Hybrid Reasoning' AI Model
LG AI Research, the AI research unit of LG, announced the launch of hybrid reasoning AI model Exaone 4.0 on July 15, 2025. Budrul Chukrut/SOPA Images/LightRocket via Getty Images LG Group, one of Korea's largest conglomerates, has unveiled a new version of its flagship AI model that can generate either a quick response to queries or produce answers using a step-by-step reasoning process. Dubbed Exaone 4.0, the hybrid AI model is developed by LG AI Research. In a statement on Tuesday, LG AI Research said Exaone 4.0 outperforms Alibaba's Qwen 3, Microsoft's Phi-4-reasoning-plus and Mistral AI's Magistral-small-2506 in maths, science and coding, citing several industry benchmarks, but lags behind DeepSeek's R1. The comparison didn't include top-tier models like OpenAI's GPT and Anthropic's Claude. LG AI Research said Exaone 4.0 can handle requests in Spanish, in addition to Korean and English. It added that Exaone 4.0 supports an increasingly popular technology called Model Context Protocol, which enables AI models to communicate with external apps, setting the stage for AI agents capable of performing complex tasks. Exaone 4.0 is freely available for research purposes and for education institutions from elementary schools to universities. LG AI Research said it's working to allow enterprises to deploy its Exaone 4.0. The launch comes as LG is diversifying its business empire that spans from home appliances, electric vehicle batteries, petrochemicals and telecommunications. Led by billionaire Koo Kwang-mo, the conglomerate last March revealed a 100 trillion won ($74 billion) five-year investment plan in South Korea's future technologies, including AI, biotech and cleantech. Since then, LG has been ramping up its AI bets. In March, its information technology service arm LG CNS announced a partnership with Nvidia-backed AI startup Cohere to develop Korean-specialized AI models for enterprises. And in January, LG Electronics teamed up with Microsoft to work on AI agents for various spaces, including homes, vehicles, hotels and offices. Despite the efforts, LG is contending with intensifying competition in Korea's AI race, which has yet to see a clear winner. The companies that are developing AI models in South Korea include billionaire Lee Hae-jin's internet giant Naver and Chey Tae-won's SK Telecom. Others are partnering with established U.S. companies. Billionaire Kim Beom-su's internet giant Kakao, for example, is working with OpenAI to develop AI agents. MORE FROM FORBES Forbes Korean Conglomerate LG To Invest $74 Billion In AI, Biotech, Cleantech And Other Growth Areas By Zinnia Lee Forbes Korean Internet Giant Kakao Teams With OpenAI To Jumpstart Growth By John Kang Forbes Nvidia-Backed AI Startup Cohere To Open Asia-Pacific Hub In South Korea By John Kang
Bloomberg
15-07-2025
- Business
- Bloomberg
South Korea's LG Unveils AI Model in Quickening Global Race
LG Group is rolling out a new version of its flagship artificial intelligence model, billing it as South Korea's first hybrid-reasoning AI system. LG AI Research announced the release of the Exaone 4.0 on Tuesday. It combines a large-language model with a reasoning AI engine capable of generating and testing hypotheses, according to a statement from LG Corp.
Geeky Gadgets
20-06-2025
- Business
- Geeky Gadgets
Gemini 2.5 Flash Hybrid Reasoning AI Optimized for AI Thinking for Efficiency
What if artificial intelligence could think only when you needed it to? Imagine a tool that seamlessly transitions between complex reasoning and straightforward processing, adapting to your specific needs without wasting resources. Enter Google's Gemini 2.5 Flash, a new AI model that redefines efficiency with its hybrid reasoning capabilities. By allowing developers to toggle between 'thinking' and 'non-thinking' modes, Gemini 2.5 Flash offers a level of control and adaptability that traditional AI systems simply can't match. Whether you're solving intricate problems or managing routine tasks, this innovation promises to deliver precision, scalability, and cost-efficiency—all tailored to your workflow. In this coverage, Prompt Engineering explore how Gemini 2.5 Flash is reshaping the AI landscape with its thinking budget optimization, multimodal processing, and enhanced token capacities. You'll discover how its unique architecture eliminates the need for separate models, streamlining operations while reducing costs. But it's not without its limitations—plateauing performance at higher token usage and capped reasoning budgets raise important questions about its scalability for resource-intensive projects. As we unpack its strengths and challenges, you'll gain a deeper understanding of whether Gemini 2.5 Flash is the right fit for your next AI endeavor. Sometimes, the real innovation lies in knowing when not to think. Gemini 2.5 Flash Overview Understanding Hybrid Reasoning At the core of Gemini 2.5 Flash lies its hybrid reasoning model, a feature that distinguishes it from traditional AI systems. This capability enables you to toggle 'thinking mode' on or off based on the complexity of the task. By managing the 'thinking budget'—the maximum number of tokens allocated for reasoning—you can optimize the model's performance to suit specific use cases. This approach eliminates the need for separate models for reasoning-intensive and simpler tasks, streamlining workflows and reducing operational overhead. Whether you're addressing intricate problem-solving scenarios or routine data processing, the model's adaptability ensures optimal performance. The ability to fine-tune the reasoning process provides a significant advantage, allowing you to allocate resources efficiently while achieving high-quality results. Cost-Efficiency and Competitive Pricing Gemini 2.5 Flash is designed with cost-conscious developers in mind, offering a pricing structure that reflects its focus on affordability and performance. The model's pricing tiers are as follows: Non-thinking mode: $0.60 per million tokens $0.60 per million tokens Thinking mode: $3.50 per million tokens This competitive pricing positions Gemini 2.5 Flash as a cost-effective alternative to other leading AI models, such as OpenAI and DeepSync. By integrating proprietary hardware and software, Google ensures a strong performance-to-cost ratio, making the model an attractive option for projects that require scalability without sacrificing quality. This balance between affordability and capability makes it a practical choice for developers aiming to optimize their resources. Gemini 2.5 Flash Hybrid Reasoning AI Model Watch this video on YouTube. Find more information on Hybrid Reasoning AI by browsing our extensive range of articles, guides and tutorials. Performance and Benchmark Comparisons In benchmark evaluations, Gemini 2.5 Flash ranks second overall on the Chatbot Arena leaderboard, trailing only OpenAI's O4 Mini in specific areas. However, it demonstrates significant improvements over its predecessor, Gemini 2.0 Flash, particularly in academic benchmarks. These advancements highlight the model's enhanced capabilities and its potential to deliver robust performance across various applications. While these results underscore its strengths, it is recommended that you test the model against your internal benchmarks to determine its suitability for your unique requirements. This hands-on evaluation will provide a clearer understanding of how Gemini 2.5 Flash can integrate into your workflows and meet your specific needs. Enhanced Token and Context Window Capabilities One of the standout features of Gemini 2.5 Flash is its enhanced token capacity, which significantly expands its utility for developers. The model supports: Maximum output token length: 65,000 tokens, making it ideal for programming tasks and applications requiring extensive outputs. 65,000 tokens, making it ideal for programming tasks and applications requiring extensive outputs. Context window: 1 million tokens, allowing the processing of large datasets or lengthy documents with ease. These enhancements provide a substantial advantage for handling complex inputs and generating detailed outputs. Whether you're working on data-heavy projects or applications requiring extensive contextual understanding, Gemini 2.5 Flash offers the tools necessary to manage these challenges effectively. Multimodal Processing for Diverse Applications Gemini 2.5 Flash extends its capabilities to multimodal processing, supporting a variety of input types, including video, audio, and images. This versatility makes it a valuable tool for industries such as media analysis, technical documentation, and beyond. However, it is important to note that the model does not include image generation features, which may limit its appeal for creative applications. Despite this limitation, its ability to process diverse input types enhances its utility across a wide range of use cases. Key Limitations to Consider While Gemini 2.5 Flash excels in many areas, it is not without its limitations. These include: Challenges with certain logical deduction tasks and variations of classic reasoning problems. A 'thinking budget' capped at 24,000 tokens, with no clear explanation for this restriction. Performance gains that plateau as token usage increases, indicating diminishing returns for resource-intensive tasks. These constraints highlight areas where the model may fall short, particularly for developers requiring advanced reasoning capabilities or higher token limits. Understanding these limitations is crucial for making informed decisions about the model's applicability to your projects. Strategic Value for Developers Google's Gemini 2.5 Flash reflects a strategic focus on cost optimization, scalability, and accessibility, making advanced AI technology available to a broader audience. Its hybrid reasoning capabilities, enhanced token and context window capacities, and multimodal processing features position it as a versatile and scalable tool for developers. By balancing quality, cost, and latency, the model caters to a wide range of applications, from data analysis to technical problem-solving. For developers seeking practical solutions that combine flexibility, performance, and affordability, Gemini 2.5 Flash offers a compelling option. Its ability to adapt to diverse tasks and optimize resource allocation ensures that it can meet the demands of modern AI challenges effectively. Media Credit: Prompt Engineering 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.
The Verge
22-05-2025
- Business
- The Verge
Anthropic's Claude 4 AI models are better at coding and reasoning
Anthropic has introduced Claude Opus 4 and Claude Sonnet 4, its latest generation of hybrid-reasoning AI models optimized for coding tasks and solving complex problems. Claude Opus 4 is Anthropic's most powerful AI model to date, according to the company's announcement, and capable of working continuously on long-running tasks for 'several hours.' In customer tests, Anthropic said that Opus 4 performed autonomously for seven hours, significantly expanding the possibilities for AI agents. The company also described its new flagship as the 'best coding model in the world,' with Anthropic's benchmarks showing that Opus 4 outperformed Google's Gemini 2.5 Pro, OpenAI's o3 reasoning, and GPT-4.1 models in coding tasks and using 'tools' like web search. Claude Sonnet 4 is a more affordable and efficiency-focused model that's better suited to general tasks, which supersedes the 3.7 Sonnet model released in February. Anthropic says Sonnet 4 delivers 'superior coding and reasoning' while providing more precise responses. The company adds that both models are 65 percent less likely to take shortcuts and loopholes to complete tasks compared to 3.7 Sonnet and they're better at storing key information for long-term tasks when developers provide Claude with local file access. A new feature introduced for both Claude 4 models is 'thinking summaries,' which condenses the chatbots' reasoning process into easily understandable insights. An 'extended thinking' feature is also launching in beta that allows users to switch the models between modes for reasoning or using tools to improve the performance and accuracy of responses. Claude Opus 4 and Sonnet 4 are available on the Anthropic API, Amazon Bedrock, and Google Cloud's Vertex AI platform, and both models are included in paid Claude plans alongside the extended thinking beta feature. Free users can only access Claude Sonnet 4 for now. In addition to the new models, Anthropic's Claude Code agentic command-line tool is now generally available following its limited preview in February. Anthropic also says it's shifting to provide 'more frequent model updates,' as the company tries to keep up with competition from OpenAI, Google, and Meta.
