LG CNS partners with W&B on agentic AI

Grok 4 is now the leading AI model and Sets New Record Despite Higher Costs Grok 4 now holds the top spot in artificial intelligence benchmarks. Developed by xAI, this model excels in multiple evaluation metrics and sets new standards for reasoning capabilities and performance. Its emergence as the leading AI model is noteworthy because it signals a shift in competitive dynamics, especially considering its pricing structure and technical features that distinguish it from rivals like Google Gemini 2.5 Pro and o3. Despite being more expensive on a per-token basis, Grok 4’s superior benchmark scores showcase its potential to redefine what’s possible with large langua #AIbenchmark #AIcomparison #AIpricing #ArtificialIntelligence #Gemini2.5Pro #Grok4 #modelperformance #o3 #xAI

DeepSeek is raising the bar again in AI innovation with its V3.2-Exp model — introducing Sparse Attention to process longer text more efficiently while cutting costs. Read more: https://lnkd.in/ddmqcdqp Hugging Face | AIResearch Ltd | Tech Innovations #DeepSeek #AI #MachineLearning #ArtificialIntelligence #DeepLearning #SparseAttention #AIInnovation #LanguageModels #AIResearch #HuggingFace #TechTrends #AIForBusiness #NextGenAI #FutureOfAI #CostEfficiency

Looks like AI chatbots are taking their debutantes to the grand ball—just hope they don’t mistake our coffee for code! This article explores Chinese AI company DeepSeek’s release of R1, a chatbot that garnered significant attention. It highlights the technological advancements and interest in AI-driven conversational tools, signaling growing global competition and innovation in the space. The piece also hints at the rapid development and potential applications of these models across industries. From a product management perspective, understanding the momentum around AI chatbots like R1 emphasizes the importance of staying ahead of emerging tech trends and focusing on user engagement to capture market share amidst competitive innovation. Thanks to Amos Zeeberg for delivering a rich and insightful look at this evolving AI landscape. #AI #Chatbots #Innovation #ProductStrategy First published: September 2025

DeepSeek introduced a groundbreaking model, V3.2-exp, which is designed to significantly reduce inference costs during long-context operations with its 'sparse attention' method. This model leverages a 'lightning indexer' to prioritize specific context and a 'fine-grained token selection system' to optimize attention window usage, thereby achieving reduced server loads. Initial tests suggest up to 50% lower API costs in long-context cases, and the model's open-weight nature invites independent assessment. Despite not causing as much disruption as deep learning advancements, it represents a step forward in cost-effective AI operation, as last seen when DeepSeek revolutionized efficiency with its R1 model. #GenerativeAi #MachineLearning #Innovation https://lnkd.in/geyFASgd

State of AI Report 2025 https://www.stateof.ai/ The State of AI Report is the most widely read and trusted analysis of key developments in AI. Published annually since 2018, the open-access report aims to spark informed conversation about the state of AI and what it means for the future. Key takeways from the 2025 Report include:: - OpenAI retains a narrow lead at the frontier, but competition has intensified as Meta reliquinshes the mantle to China’s DeepSeek, Qwen, and Kimi close the gap on reasoning and coding tasks, establishing China as a credible #2. - Reasoning defined the year, as frontier labs combined reinforcement learning, rubric-based rewards, and verifiable reasoning with novel environments to create models that can plan, reflect, self-correct, and work over increasingly long time horizons. - AI is becoming a scientific collaborator, with systems like DeepMind’s Co-Scientist and Stanford’s Virtual Lab autonomously generating, testing, and validating hypotheses. In biology, Profluent’s ProGen3 showed that scaling laws now apply to proteins too. - Structured reasoning entered the physical world through “Chain-of-Action” planning, as embodied AI systems such as AI2’s Molmo-Act and Google’s Gemini Robotics 1.5 began to reason step-by-step before acting. - Commercial traction accelerated sharply. Forty-four percent of U.S. businesses now pay for AI tools (up from 5% in 2023), average contracts reached $530,000, and AI-first startups grew 1.5× faster than peers, according to Ramp and Standard Metrics. - Our inaugural AI Practitioner Survey, with over 1,200 respondents, shows that 95% of professionals now use AI at work or home, 76% pay for AI tools out of pocket, and most report sustained productivity gains, evidence that real adoption has gone mainstream. - The industrial era of AI has begun. Multi-GW data centers like Stargate signal a new wave of compute infrastructure backed by sovereign funds from the U.S., UAE, and China, with power supply emerging as the new constraint. - AI politics hardened further. The U.S. leaned into “America-first AI,” Europe’s AI Act stumbled, and China expanded its open-weights ecosystem and domestic silicon ambitions. - Safety research entered a new, more pragmatic phase. Models can now imitate alignment under supervision, forcing a debate about transparency versus capability. External safety organizations, meanwhile, operate on budgets smaller than a frontier lab’s daily burn. - The existential risk debate has cooled, giving way to concrete questions about reliability, cyber resilience, and the long-term governance of increasingly autonomous systems.

AI is developing so fast that it can no longer keep up. I came across two reports about AI, where you can immediately see the summary. 1. State of AI Report 2025 (https://www.stateof.ai/) Key findings from the 2025 Report: OpenAI retains a slight lead, but competition has intensified: Meta has lost the lead to Chinese companies DeepSeek, Qwen and Kimi, which are closing the gap in reasoning and coding tasks, asserting China as a strong "number 2". Reasoning has become crucial this year, as leading labs have combined reinforcement learning, category-based reward, and testable reasoning with new environments to create models capable of planning, reflecting, self-correcting, and operating over increasingly long time horizons. Artificial intelligence becomes a researcher: systems such as DeepMind's Co-Scientist and Stanford's Virtual Lab autonomously generate, test, and validate hypotheses. In biology, Profluent's ProGen3 has shown that scaling laws are now applicable to proteins as well. Structured reasoning has entered the physical world thanks to Chain-of-Action planning, as embodied AI systems such as AI2's Molmo-Act and Google's Gemini Robotics 1.5 have begun to reason step-by-step before performing actions. Commercial adoption has accelerated dramatically. Forty-four percent of American companies are now paying for AI tools (up from 5% in 2023), the average contract amount has reached $530,000, and AI-first startups have grown 1.5 times faster than their competitors, according to Ramp and Standard Metrics. Our first survey of AI practitioners with more than 1,200 respondents found that 95% of professionals now use AI at work or at home, 76% pay for AI tools out of pocket, and most report steady productivity gains — evidence that real adoption has become widespread. The industrial era of AI has begun. Multi-gigawatt data centers like Stargate are signaling a new wave of computing infrastructure backed by U.S., UAE, and Chinese sovereign wealth funds, with power supply becoming a new limiting factor. AI policy has become even tougher. The United States has focused on "AI first for America" (America-first AI), the EU AI Act has stalled, and China has expanded its ecosystem of open-scale models and ambitions for domestic chip production. Security research has entered a new, more pragmatic phase. Models can now simulate alignment under control, which raises a debate about transparency versus capability. Meanwhile, external security organizations operate with budgets lower than the daily costs of the lead laboratory. The debate about existential risk has subsided, giving way to specific questions about reliability, cyber resilience, and the long-term management of increasingly autonomous systems.

This article introduces Agentic RAG, an evolution in AI systems that enhances standard RAG by incorporating smart AI agents for dynamic workflows. I found it interesting that these agents can not only choose the most suitable tools for queries but also verify their own responses, promoting greater accuracy and flexibility. How do you see these advancements impacting your work or industry?

💥💥💥 STATE OF AI REPORT 2025 | Nathan Benaich Key takeways from the 2025 Report include: ➡️ OpenAI retains a narrow lead at the frontier, but competition has intensified as Meta reliquinshes the mantle to China’s DeepSeek, Qwen, and Kimi close the gap on reasoning and coding tasks, establishing China as a credible #2. ➡️ Reasoning defined the year, as frontier labs combined reinforcement learning, rubric-based rewards, and verifiable reasoning with novel environments to create models that can plan, reflect, self-correct, and work over increasingly long time horizons. ➡️ AI is becoming a scientific collaborator, with systems like DeepMind’s Co-Scientist and Stanford’s Virtual Lab autonomously generating, testing, and validating hypotheses. In biology, Profluent’s ProGen3 showed that scaling laws now apply to proteins too. ➡️ Structured reasoning entered the physical world through “Chain-of-Action” planning, as embodied AI systems such as AI2’s Molmo-Act and Google’s Gemini Robotics 1.5 began to reason step-by-step before acting. ➡️ Commercial traction accelerated sharply. Forty-four percent of U.S. businesses now pay for AI tools (up from 5% in 2023), average contracts reached $530,000, and AI-first startups grew 1.5× faster than peers, according to Ramp and Standard Metrics. ➡️ Our inaugural AI Practitioner Survey, with over 1,200 respondents, shows that 95% of professionals now use AI at work or home, 76% pay for AI tools out of pocket, and most report sustained productivity gains, evidence that real adoption has gone mainstream. ➡️ The industrial era of AI has begun. Multi-GW data centers like Stargate signal a new wave of compute infrastructure backed by sovereign funds from the U.S., UAE, and China, with power supply emerging as the new constraint. ➡️ AI politics hardened further. The U.S. leaned into “America-first AI,” Europe’s AI Act stumbled, and China expanded its open-weights ecosystem and domestic silicon ambitions. ➡️ Safety research entered a new, more pragmatic phase. Models can now imitate alignment under supervision, forcing a debate about transparency versus capability. External safety organizations, meanwhile, operate on budgets smaller than a frontier lab’s daily burn. ➡️The existential risk debate has cooled, giving way to concrete questions about reliability, cyber resilience, and the long-term governance of increasingly autonomous systems. Video 👉 https://lnkd.in/dJ5TuTbc Report 👉 https://www.stateof.ai/ #machinelearning

Did you know there are AI models beyond LLMs and artificial neural networks? In this article published on the Nuxia blog, I discuss explainable AI models, powerful strategies for problems where explainability is a non-negotiable. Check it out and discover how AI can be trustworthy for applications in systems monitoring or key decision-making..

Well, if AI chatbots aren't taking over product management meetings yet, they soon will be—maybe as the new voice of reason! This article dives into DeepSeek's release of R1, a chatbot from China that’s stirring quite a buzz, highlighting the rapid innovation in AI-driven conversational tools and their growing influence in tech landscapes. It emphasizes how Chinese AI companies are making big waves, with R1 showcasing advanced capabilities, and signals a trend towards more sophisticated, culturally nuanced AI products. As a product manager, this reminds me that staying ahead of global AI developments can be a game-changer for product strategy and user engagement, especially considering how geopolitics can influence market opportunities. Thanks to Amos Zeeberg for unpacking this intriguing glimpse into the future of conversational AI. #AI #Innovation #ProductStrategy #Chatbots First published: September 2025