Latest news with #GenAI-based
Economic Times
2 days ago
- Business
- Economic Times
DeepSeek can undercut larger ChatGPT, ace investor Mary Meeker warns
Mary Meeker predicts AI will spawn numerous trillion-dollar companies, with competition intensifying from firms like China's DeepSeek. Rising training costs for leading US models, such as OpenAI's GPT, are creating opportunities for cheaper, task-specific alternatives. The current AI landscape resembles a capital-intensive commodity market, demanding deep funding and patient investors for startups to thrive. Tired of too many ads? Remove Ads Tired of too many ads? Remove Ads Artificial intelligence (AI) forerunners like OpenAI could soon face serious competition from cheaper rivals such as China's DeepSeek , according to renowned Silicon Valley analyst and investor Mary Meeker Meeker, an early investor in companies like Meta, Spotify, and Airbnb, told the Financial Times that AI will create 'multiple companies worth $10 trillion' — and not all of them will be based in North America. 'The wealth creation will be extraordinary. We've never had a five-billion-user market that was this easy to reach,' she a recent report, Meeker and others point out that US companies, such as OpenAI's GPT and Google's Gemini, leading the development of large language models (LLMs) are now facing rising training costs. At the same time, competition from players like DeepSeek has intensified.'The business model is in flux,' Meeker wrote. 'Smaller, cheaper models tailored for specific tasks are emerging, challenging the idea that one large, general-purpose LLM can do it all.'While AI companies have enjoyed rise in revenues and stock prices, they face growing threats. New, more powerful chips and improved algorithms are lowering the cost of running AI models. This is helping competitors like DeepSeek launch models that are more affordable and goes on to underscore that, in the short term, these AI businesses are starting to look like commodity operations that burn through venture capital at a rapid pace. Despite the advances in the space, training the most advanced AI models is still extremely expensive. Costs have increased 2,400 times in the past eight years, making it nearly impossible for smaller players to compete. Only a few companies can afford to keep up, and even those lack a clear path to lower prices and more model options benefit consumers, they create a tough environment for startups. To survive, these companies need deep funding and patient investors. Meeker compares their situation to companies like Uber, Amazon, and Tesla , which all spent heavily for years before turning a reported earlier this week how several Indian startups may have to tap external funding to scale up their GenAI-based applications as AI companies such as OpenAI and Anthropic pause steep price cuts of their generative AI rose to fame during her time at Morgan Stanley with bets like Google and Apple, earning the moniker "queen of the internet". She joined venture capital firm Kleiner Perkins in 2010 and later co-founded her own firm, Bond, in 2019.
Time of India
3 days ago
- Business
- Time of India
DeepSeek can undercut larger ChatGPT, ace investor Mary Meeker warns
Artificial intelligence (AI) forerunners like OpenAI could soon face serious competition from cheaper rivals such as China's DeepSeek , according to renowned Silicon Valley analyst and investor Mary Meeker . Meeker, an early investor in companies like Meta, Spotify, and Airbnb, told the Financial Times that AI will create 'multiple companies worth $10 trillion' — and not all of them will be based in North America. 'The wealth creation will be extraordinary. We've never had a five-billion-user market that was this easy to reach,' she added. In a recent report, Meeker and others point out that US companies, such as OpenAI's GPT and Google's Gemini, leading the development of large language models (LLMs) are now facing rising training costs. At the same time, competition from players like DeepSeek has intensified. 'The business model is in flux,' Meeker wrote. 'Smaller, cheaper models tailored for specific tasks are emerging, challenging the idea that one large, general-purpose LLM can do it all.' While AI companies have enjoyed rise in revenues and stock prices, they face growing threats. New, more powerful chips and improved algorithms are lowering the cost of running AI models. This is helping competitors like DeepSeek launch models that are more affordable and efficient. Live Events She goes on to underscore that, in the short term, these AI businesses are starting to look like commodity operations that burn through venture capital at a rapid pace. Despite the advances in the space, training the most advanced AI models is still extremely expensive. Costs have increased 2,400 times in the past eight years, making it nearly impossible for smaller players to compete. Only a few companies can afford to keep up, and even those lack a clear path to profitability. Discover the stories of your interest Blockchain 5 Stories Cyber-safety 7 Stories Fintech 9 Stories E-comm 9 Stories ML 8 Stories Edtech 6 Stories While lower prices and more model options benefit consumers, they create a tough environment for startups. To survive, these companies need deep funding and patient investors. Meeker compares their situation to companies like Uber, Amazon, and Tesla , which all spent heavily for years before turning a profit. ET reported earlier this week how several Indian startups may have to tap external funding to scale up their GenAI-based applications as AI companies such as OpenAI and Anthropic pause steep price cuts of their generative AI models. Meeker rose to fame during her time at Morgan Stanley with bets like Google and Apple, earning the moniker "queen of the internet". She joined venture capital firm Kleiner Perkins in 2010 and later co-founded her own firm, Bond, in 2019.
Hans India
3 days ago
- Business
- Hans India
Beyond resumes: How Gen AI is redefining recruitment
Recruitment is undergoing a tech revolution, with HR leaders embracing generative AI at every stage of hiring. From context-driven resume screening to AI-enabled interviews and adaptive assessments, the technology is boosting efficiency, accuracy, and candidate experience. As tools like and HireVue take the lead, recruiters are finding more time to focus on what matters most: understanding people beyond the paper HR professionals are proving to be some of the keenest adopters of generative AI technology. According to recent research by Gartner, 38% of HR leaders are already piloting, planning, or implementing Gen AI initiatives. With use cases spanning resume screening, candidate engagement, assessments, and internal operations, generative AI is quickly becoming a valuable partner in the recruitment process. As organizations explore its growing capabilities, AI is set to reshape how talent is sourced, evaluated, and managed—enhancing efficiency while keeping human judgment at the core. Impact of Gen AI on recruitment Recruitment is seeing a change with AI-driven tools optimizing various aspects, from application tracking to candidate engagement. Traditional applicant tracking systems (ATS) have long relied on keyword matching and fixed filters to screen resumes. While they are efficient at handling large volumes, they often miss qualified candidates who do not use the exact terms expected. Generative AI is shifting this approach by focusing on context and intent rather than just word matches. For instance, LinkedIn Recruiter's AI assistant can identify candidates with transferable skills and relevant career progressions—even if their job titles don't directly match the role. A data analyst might still be a strong fit for a business intelligence position based on their tools and outcomes. Platforms like take it further by reading between the lines. If a candidate led a CRM migration, the system can infer related skills such as data integration, change management, and customer lifecycle strategy—even if these are not explicitly mentioned. Some tools also generate plain-language summaries of candidate profiles, giving recruiters a quick, clear snapshot of strengths without needing to decode jargon. Others, like HireVue, enhance the process with AI-integrated video interviews to assess communication skills and simulate real-world scenarios. Gen AI based automated proctored assessments Once candidates are shortlisted, they undergo written tests to evaluate aptitude, technical knowledge, and behavioral traits. These tests go beyond technical proficiency—they also assess cultural fit, adaptability, and problem-solving ability. For instance, Capgemini uses AI-powered assessments to evaluate domain expertise and cognitive skills, resulting in a 40% improvement in hiring efficiency. However, Gen AI-based assessments bring a deeper layer of intelligence and adaptability to the process. Unlike traditional AI, Gen AI systems are capable of learning continuously, recognizing patterns, making contextual decisions, and evolving over time—similar to human cognition. This means Gen AI can detect subtle anomalies, adapt to new test-taking behaviors, and refine its proctoring mechanisms with each session. For example, it can use facial recognition to flag impersonation attempts, or analyze eye movement, facial expressions, and typing patterns to detect potential cheating. Over time, these models become smarter, making the evaluation process more secure, unbiased, and scalable. Gen AI-enabled interviews AI is reshaping interviews through automated scheduling and AI-led interactions. Platforms like Incruiter use natural language processing (NLP) to assess responses for tone, confidence, and coherence, offering recruiters structured insights. For example, Unilever's AI-driven interviews evaluate facial expressions, speech patterns, and word choice—cutting hiring time by 75%. Gen AI builds on this by enabling adaptive, dynamic interviews. Instead of asking preset questions, the system can tailor follow-ups based on a candidate's previous answers. It recognizes context, adjusts in real time, and improves with each interaction. For example, HireVue uses Gen AI to simulate real-world scenarios, offering role-specific questions and evaluating not just what candidates say, but how they think and respond under pressure. Rise of agentic AI in HR AI is progressing beyond assistance to autonomous execution. Agentic AI independently handles multi-step HR tasks—such as sourcing, screening, and scheduling—minimizing manual input. HireVue, for example, uses asynchronous AI interviews to evaluate candidates using speech and facial analysis. Goodspace AI monitors employee wellness, predicts engagement drops, and suggests interventions. SourceBae deploys agentic AI to autonomously source and vet tech candidates. In one case, a mid-sized tech firm seeking React developers used Agentic AI to source 80 candidates, screen 30 via chatbot-led interviews, and schedule 10 for finals—cutting recruiter workload by 60% and time-to-hire by 40%. These systems also support retention and workforce planning by learning continuously, making them particularly valuable in fast-growing or lean HR environments. Generative AI is set to permeate the entire recruitment lifecycle—from screening to onboarding—playing a key role in driving both productivity and quality in hiring. Routine tasks and standard activities will increasingly be handled by AI, allowing HR professionals to focus on high-value areas such as behavioral assessment, cultural fit, and strategic decision-making.
Time of India
6 days ago
- Business
- Time of India
Top AI firms pivot to profitability track leaving price wars behind
With artificial intelligence companies such as OpenAI and Anthropic pausing steep price cuts of their generative AI models , several Indian startups may have to tap external funding to scale up their GenAI-based applications. OpenAI, Anthropic and Google — which reduced GenAI model pricing by 65%-90% in 2024 — are releasing new models at roughly flat or even higher rates. Experts said the cost of intelligence may still go down going forward, albeit at a slower rate because model companies are no longer hustling to train new models month after month. Instead, they are competing in the application layer with agents and enterprise AI. ETtech This is limiting the ability of Indian startups to scale AI applications, invest in R&D, and pass on cost savings to customers. Companies are shifting to more efficient and smarter AI usage to overcome the challenge while experts say most may have to tap external funding in the long term. Live Events "Cost is definitely a challenge right now, especially when scaling AI agents that require high inference loads, long context windows, memory, and tool use," said Somit Srivastava, CTO at a wealthtech platform. "Running production-grade agents at scale isn't cheap, and it impacts pricing strategies, performance tuning, and R&D investment decisions." Discover the stories of your interest Blockchain 5 Stories Cyber-safety 7 Stories Fintech 9 Stories E-comm 9 Stories ML 8 Stories Edtech 6 Stories He said has largely relied on open-source models which are free to use instead of paid alternatives. But there's a constant trade-off between performance versus viable cost-to-serve through open models. Many startups can't afford continuous improvement cycles without solid funding, said Arun Chandrasekaran, distinguished VP analyst at Gartner. Cutting-edge GenAI research and development (R&D) such as agent architecture, long-context models, and tool use, are compute-intensive and not easily subsidised by commercial revenues yet, he said. "Many teams are forced to 'build wrappers' instead of innovating, or to anchor themselves to public APIs to reduce infra lift," Chandrasekaran said. Experts said startups need to act early and design intelligently, and not just wait for prices to fall. Abhimanyu Singh, vice president-product at GenAI-based customer support platform said cost is becoming a primary scaling bottleneck, especially for agentic applications requiring multiple model calls.
Yahoo
14-05-2025
- Business
- Yahoo
Quest Unveils AI Governance Solution Designed to Build Enterprise Data Trust
New Release Offers Automated AI Model Certification, Role-Based Data Experience, and GenAI-based Stewardship Tools in Preview AUSTIN, Texas, May 14, 2025 (GLOBE NEWSWIRE) -- Quest Software, a global leader in protecting critical IT assets, powering data for AI and analytics, and modernizing Microsoft and database platforms, today announced erwin Data Intelligence 15 - a major update to its AI governance platform. The new version gives organizations the tools to build trust in their data by certifying AI models, improving discovery, and reducing the manual effort of data governance. The release comes at a time when organizations face growing pressure to ensure AI-driven decisions are transparent, explainable, and based on reliable data. Why it Matters Without strong governance and trustworthy data, AI projects often fail. Gartner predicts that 30% of Generative AI projects will be abandoned after proof of concept by end of 2025. This gap between plans and reality often comes down to foundational issues like data readiness. erwin Data Intelligence 15 addresses these issues with automated AI model certification, a personalized data discovery experience, and new GenAI tools to accelerate governance tasks. 'As companies work to put AI into production, they face one critical question: Is our data good enough to trust the outcome?' said Bharath Vasudevan, Vice President of Product at Quest Software. 'This release helps companies confidently answer 'yes'. We provide the tools to certify AI models, quickly surface the most valuable data, and spend less time managing.' Quest's automated approach to AI model certification is already gaining industry attention for its ability to significantly improve AI readiness and trust. 'Automated AI model certification in erwin Data Intelligence 15 offers organizations greater visibility into the readiness and reliability of AI models and their supporting data,' said Stewart Bond, VP of Data Intelligence and Integration Software at IDC. 'This centralized approach to AI governance can help organizations advance their AI data readiness initiatives, supporting more successful AI outcomes while addressing regulatory and operational risks.' What's New in erwin Data Intelligence 15 AI Model Certification Certify AI models using Quest's structured seven-step framework—built into erwin Data Intelligence 15 -- as the only solution that automates AI model certification through data intelligence. It goes beyond basic tracking or compliance, guiding teams through a consistent process to move trusted models into production. Automatically track model maturity and data quality using a configurable certification framework. Classify AI models into customizable maturity tiers, with status visible to both governance and data science teams for centralized oversight. Data Valuation and Trust Scoring Score data using up to nine weighted criteria—including quality, relevance, usage, and governance completeness. Customize the weight of each based on business goals, and automatically generate a value score to highlight trusted, high-value assets. Assign gold, silver, or bronze tiering to make data value scores easy to recognize at a glance. Supports data monetization by making high-value data easier to discover and use. Role-Based Access to Marketplace Insights Persona-based landing pages in erwin Data Marketplace to accelerate discovery and governance of relevant assets. Choose from a library of ready-to-use visualizations for quick insights and filter results by asset type—such as data products, AI models, or business policies. Gain actionable insights on assets that are recently curated, highly scored, recommended, or require attention to improve the speed and efficiency of governance. Bonus for existing Microsoft Customers erwin Data Intelligence 15 includes a new erwin Standard Data Connector for Microsoft Dataverse. This allows organizations to ingest metadata from Dataverse, to gain visibility across their Microsoft data landscape while applying all of erwin's capabilities, including AI model certification, automated governance, trust scoring, and data marketplace integration. erwinAI - GenAI that lightens the load for Data Stewards Launching in preview alongside the erwin Data Intelligence 15 release, erwinAI is a GenAI-powered agentic chatbot that reduces manual governance with new data stewardship accelerators. This reduces manual effort and helps close governance gaps faster. Initial capabilities include: Speeding up the classification of tables and columns and tlp generation of business term definitions. Stewards can quickly spot missing classifications and incomplete definitions, then review, approve, and apply suggested updates—all through the agentic chatbot, with full audit trail support. Additional erwinAI capabilities will roll out throughout 2025, bringing new stewardship and discovery accelerators designed to make data governance smarter and more intuitive. How Quest Stands Apart Quest's erwin Data Intelligence provides automated, structured AI model certification and flexible, weighted data scoring, both based on governance best practices. Where others rely primarily on workflow tracking or usage analytics, erwin delivers comprehensive visibility into AI model readiness, data value, and governance status—in one platform. To explore all the features of erwin Data Intelligence 15 by Quest: Visit the erwin Data Intelligence page and watch the "What's New in erwin Data Intelligence 15" video: Register to attend the 'Introducing erwin Data Intelligence 15' webinar on June 4: Visit the erwin AI governance solutions page and watch the video to see how erwin supports AI governance: Watch the erwin Data Marketplace video to see the new user experience: About Quest SoftwareQuest creates software solutions that make the benefits of new technology real in an increasingly complex IT landscape. From database and systems management to Active Directory and Microsoft 365 migration and management, and cybersecurity resilience, Quest helps customers solve their next IT challenge now. Around the globe, more than 130,000 companies and 95% of the Fortune 500 count on Quest to deliver proactive management and monitoring for the next enterprise initiative, find the next solution for complex Microsoft challenges, and stay ahead of the next threat. For more information, visit Media contact:Slava BalykovPR 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
