Latest news with #Programming
&w=3840&q=100)
Business Standard
11-06-2025
- Business
- Business Standard
OpenAI delays launch of its open-weight AI model: All you need to know
OpenAI has delayed the release of its open-weight model, which was initially expected to be released in early summer. CEO Sam Altman announced the delay through a post on X (formerly Twitter) on June 11, stating 'we are going to take a little more time with our open-weights model, i.e. expect it later this summer but not June." Altman shared that the delay comes as a result of unexpected progress made by OpenAI's research team. He explained 'Our research team did something unexpected and quite amazing, and we think it will be very, very worth the wait, but needs a bit longer.' we are going to take a little more time with our open-weights model, i.e. expect it later this summer but not june. our research team did something unexpected and quite amazing and we think it will be very very worth the wait, but needs a bit longer. — Sam Altman (@sama) June 10, 2025 OpenAI's open-weight model: What to expect The upcoming open model is said to feature reasoning capabilities on par with OpenAI's o-series models and aims to outperform other leading open reasoning models like DeepSeek's R1. OpenAI is exploring advanced features to strengthen its open model. According to a report by TechCrunch, one possibility includes integrating the model with OpenAI's cloud-based systems for handling complex tasks. However, it remains uncertain whether such capabilities will be part of the final release. What are open-weight language models? Open-weight language models are AI systems whose trained parameters—the numerical values that guide how the model operates—are openly shared with the public. This enables researchers, developers, and organisations to download and use the models on their own devices, without needing access to a cloud-based API (Application Programming Interface). However, such models can still come with licensing limitations, especially around modifications and commercial applications. How are they different from other models? Open-weight models strike a balance between fully open-source and entirely closed AI systems. Unlike open-source models that offer complete access to both code and model weights with minimal restrictions, open-weight models typically release only the trained weights and may include limitations on how they can be modified or used commercially. On the other hand, closed models like OpenAI's GPT-4 and Google's Gemini keep both their code and weights private, maintaining full proprietary control over their technology.
New Indian Express
07-06-2025
- Business
- New Indian Express
'AI models can hallucinate or misfire'
Artificial Intelligence (AI) offers immense potential, but it's not without challenges. Mohit Saxena, Co-Founder & CTO, InMobi & Glance told TNIE that there's the critical need for human oversight and that AI models can hallucinate or misfire, and in today's sensitive digital climate, ensuring responsible output is essential. 'We're investing in rigorous moderation infrastructure and developing new governance frameworks to mitigate these risks,' he said. He added that deep AI expertise is scarce. 'While surface-level applications like RAG (Retrieval-Augmented Generation) are becoming common, true innovation requires depth in data science, ML infrastructure, and systems thinking—talent that's still hard to find.' But our global presence in Bengaluru, San Francisco, and the UK gives us broader access to specialised talent pools, the co-founder said. Talking about other key challenges, he said that AI infrastructure is expensive. Running advanced models at scale demands significant compute and energy. 'Our approach is rooted in frugality—we optimize model usage, leverage pre-processing, explore alternatives like TPUs (Tensor Processing Unit), and work closely with partners like Google to get the most out of every dollar,' he said. InMobi views AI not just as a tool, but as a foundational shift and its roadmap over the next one to three years is anchored in three key areas. 'First, we are reimagining engineering productivity with AI—helping experienced engineers scale faster and empowering fresh talent to leapfrog traditional learning curves. AI is now embedded into every aspect of how we build—whether it's writing code, improving observability, or boosting efficiency,' he said. 'Second, we are building intelligent automation into our core business processes—moving from simple scripting to AI agents that can deconstruct complex workflows, predict outcomes, and take action. This isn't just automation; it's autonomous decision-making at scale. Third, we're embracing the rise of agentic architecture—where agents talk to agents, not APIs (Application Programming Interface), to get work done. This is the future of system communication, and are actively developing for it,' he further said. InMobi is setting up a dedicated unit to track and accelerate engineering efficiency with AI, with a goal to complete most of the foundational work by year-end. The company is leveraging AI to generate high-impact formats—ranging from image-based ads to audio creatives—enabling brands to engage users across multiple touchpoints. It also uses AI to generate and summarize content at scale. In the visual content space, he said the company is leveraging Contrastive Language-Image Pre-training (CLIP) to bridge the gap between AI-generated creativity and real-world commerce through its Glance AI product. 'By using CLIP, we're able to understand and interpret AI-generated fashion looks—essentially decoding the visual style and identifying apparel elements within the image. These elements are then matched to real products from our extensive catalogue of brand and retail partners,' he explained. Even before the LLM (large language model) wave, the company has been leveraging AI for content generation at Glance. 'We're onboarding fresh engineering talent through structured bootcamps where AI adoption starts from day one—including access to AI assistants and hands-on experience with applied ML tools. Simultaneously, we're deepening our bench strength by hiring top-tier data scientists—we've onboarded over 50 employees in the past year alone, across domains like LLMs, DNNs (Deep Neural Networks), and imaging. We're also shifting our hiring lens—prioritising engineers with a strong aptitude in data science and statistical thinking. Our aim is that 80% of our workforce, both new and existing, to be highly AI- and ML-savvy in the next 1–2 years,' the co-founder and CTO informed.
Yahoo
06-06-2025
- Business
- Yahoo
Alibaba Releases New Open-Source AI Models With Multilingual And Code Support
Alibaba Group Holding (NYSE:BABA) has made its Qwen3 Embedding series available for developers as open-source artificial intelligence (AI) models become more popular. The series marks another addition to the company's line-up of large language models (LLMs), SCMP reported on Friday. Alibaba's new models 'support over 100 languages, including multiple programming languages, and provide robust multilingual, cross-lingual and code retrieval capabilities.'Alibaba said the new series would enable ongoing optimization of the Qwen foundation model, resulting in enhanced training and improved efficiency of its embedding and reranking systems. Alibaba Cloud founder Wang Jian said AI will evolve faster than expected and be driven by young innovators solving complex problems. He expects AI to develop at a pace beyond people's imagination in the next five, 10, and even 50 years, citing examples like DeepSeek. He had said the capabilities of existing LLMs are far above prior expectations. In May, Alibaba showcased ZEROSEARCH technology, which it said can cut AI training costs by nearly 90% by helping LLMs simulate search behavior without making actual Application Programming Interface calls to search engines during the training process. Benchmark analyst Fawne Jiang noted Alibaba as a leading beneficiary of accelerated AI adoption in China and a top structural player in the sector. The global open-source intelligence market size was worth $14.4 billion in 2024. IMARC Group expects the market to reach $58.0 billion by 2033, at a CAGR of 15.93% from 2025-2033, driven by higher cyber security threats, expansion of e-commerce and online platforms channels, and the implementation of AI security solutions to enrich decision-making processes and address risks within the evolving digital environment. Price Action: Alibaba shares traded lower by 0.85% at $118.91 at publication on Friday. Read Next:Photo by via Shutterstock UNLOCKED: 5 NEW TRADES EVERY WEEK. Click now to get top trade ideas daily, plus unlimited access to cutting-edge tools and strategies to gain an edge in the markets. Get the latest stock analysis from Benzinga? ALIBABA GR HLDGS (BABA): Free Stock Analysis Report This article Alibaba Releases New Open-Source AI Models With Multilingual And Code Support originally appeared on © 2025 Benzinga does not provide investment advice. All rights reserved. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
&w=3840&q=100)
Business Standard
30-05-2025
- Business
- Business Standard
Siddaramaiah launches real-time 'CM Dashboard' for development monitoring
The 'Chief Minister's Dashboard' (CM Dashboard), a platform that provides real-time, integrated insights into key development indicators across Karnataka was launched on Friday. It was launched by Chief Minister Siddaramaiah during the review meeting with Deputy Commissioners of all districts and CEOs of all Zilla Panchayats at Vidhana Soudha, the seat of the state legislature and secretariat here. The dashboard, developed in-house by the Centre for e-Governance (CeG), is now functionally complete and hosted under the domain This platform provides real-time, integrated insights into key development indicators across Karnataka, enabling data-driven governance and decision-making at the highest level, an official release said. The dashboard is built using a microservices-based architecture, ensuring scalability and ease of integration, and the data is integrated via APIs (Application Programming Interface) from various departments, eliminating manual entry. According to officials, the dashboard categorises state performance data into four primary sectors: Economic Growth (e.g., investments, beneficiaries), Legal/Judiciary Management (e.g., RTI, Sakala case disposals), Infrastructure Development (e.g., roads, irrigation, renewable energy), and Citizen-Centric Governance (e.g., Guarantee Schemes, Janaspandana). Designed to promote transparency, the portal displays real-time progress metrics and enables public access to key schemes and service outcomes, they said. (Only the headline and picture of this report may have been reworked by the Business Standard staff; the rest of the content is auto-generated from a syndicated feed.)
Economic Times
30-05-2025
- Business
- Economic Times
Karnataka's Siddaramaiah launches real-time 'CM Dashboard' for development monitoring
Agencies Karnataka CM Siddaramaiah The 'Chief Minister's Dashboard' (CM Dashboard), a platform that provides real-time, integrated insights into key development indicators across Karnataka was launched on Friday. It was launched by Chief Minister Siddaramaiah during the review meeting with Deputy Commissioners of all districts and CEOs of all Zilla Panchayats at Vidhana Soudha, the seat of the state legislature and secretariat here. The dashboard, developed in-house by the Centre for e-Governance (CeG), is now functionally complete and hosted under the domain This platform provides real-time, integrated insights into key development indicators across Karnataka, enabling data-driven governance and decision-making at the highest level, an official release said. The dashboard is built using a microservices-based architecture, ensuring scalability and ease of integration, and the data is integrated via APIs (Application Programming Interface) from various departments, eliminating manual entry. According to officials, the dashboard categorises state performance data into four primary sectors: Economic Growth (e.g., investments, beneficiaries), Legal/Judiciary Management (e.g., RTI, Sakala case disposals), Infrastructure Development (e.g., roads, irrigation, renewable energy), and Citizen-Centric Governance (e.g., Guarantee Schemes, Janaspandana). Designed to promote transparency, the portal displays real-time progress metrics and enables public access to key schemes and service outcomes, they said.
