Latest news with #DataStax
TechCrunch
28-05-2025
- Business
- TechCrunch
Shape the Disrupt 2025 agenda: Vote for your favorite sessions
We were blown away by the incredible interest in speaking at TechCrunch Disrupt 2025, happening October 27–29 at Moscone West in San Francisco. After a thorough review, we've narrowed it down to 20 standout finalists—10 for breakout sessions and 10 for roundtables. Now it's your turn to decide. Audience Choice voting is open through May 30 at 11:59 p.m. PT. You can cast one vote per session—and vote for as many sessions as you like! The top 5 breakout and top 5 roundtable sessions will earn a spot on the Disrupt agenda. Image Credits:TechCrunch Meet the finalists Breakout Sessions How to Get Acquired in Tech (Without Selling Out): M&A Tips for Founders and Builders Aklil Ibssa, Head of Corporate Development and M&A, Coinbase Agentic AI for Startups: Automate, Adapt, and Accelerate Growth Anmol Rastogi, Head of Product, Amazon Business — AI & ML, Amazon Automation with Agents: From Work Enablement to Work Completion Chet Kapoor, Chairman and CEO, DataStax Techcrunch event Join us at TechCrunch Sessions: AI Secure your spot for our leading AI industry event with speakers from OpenAI, Anthropic, and Cohere. For a limited time, tickets are just $292 for an entire day of expert talks, workshops, and potent networking. Exhibit at TechCrunch Sessions: AI Secure your spot at TC Sessions: AI and show 1,200+ decision-makers what you've built — without the big spend. Available through May 9 or while tables last. Berkeley, CA | REGISTER NOW AI at the Brink: Strategic Playbook for National Security Dan Hendrycks, Executive and Research Director, Center for AI Safety (CAIS) Leading a Series A Round in 2025 and Sustaining Momentum Gabriel Kra, Managing Director, Prelude Ventures The Agentic Apocalypse: Securing the Enterprise in the Age of 1 Billion AI Agents Jack Hidary, CEO, SandboxAQ; and Jim Breyer, Founder and CEO, Breyer Capital Embracing AI for a Better Digital Future Matt Madrigal, Chief Technology Officer, Pinterest Mining for Millions with GenAI's 4 Ds: Striking Trust, Delight, and Dividends Michael Stewart, Managing Partner, M12 From Data to Agents: Building the AI-Native Enterprise Sridhar Ramaswamy, Chief Executive Officer, Snowflake From Vibes to Velocity: How AI Tools Can Help You Achieve Your Development Goals Tim Rogers, Staff Product Manager, GitHub Copilot, GitHub Roundtable Sessions Future of Space Economy in the Low Earth Orbit Abhijeet Kumar, Invited Lecturer — New Space Economy, UC Berkeley | Tech and Strategy Lead, Archer From Startup to Scale-Up: A GTM Blueprint Anjai Lal, Head of Strategy and Enablement, Google Cloud From Code to Capital: How VCs Spot the Next AI Powerhouses Avi Bharadwaj, Investment Director, Intel Capital The Winning Formula: Turning Your Business into a Trusted, Scalable Community to Drive Growth Justine Palefsky and Tasneem Amina, Co-founders, Kindred; and Vlad Loktev, Partner, Index Ventures How to Train Your Model: Taming AI Agents Without Breaking Them Kyla Guru, Head of Model Cyber Policy, Anthropic; and Alex Moix, Investigations Lead, Safeguards, Anthropic Going a Layer Deeper: Why the Future of AI Investments Lies with Infrastructure and Applications Paul Drews, Managing Partner, Salesforce Ventures Scaling Search and AI for Millions: Lessons from Reddit Search Rachel Miller, Product Manager, Reddit AI Evaluation 101: Addressing Challenges to Real-World AI Applications Rohit Patel, Director, Generative AI, Meta From Workarounds to Breakthroughs: How UpLink Lets Users Connect Any App—No Integration Needed Scott Weinert, CTO and Co-founder, Atomic Whose Company Is It, Anyway?: What You Lose When You Accept Outside Capital Sridhar Vembu, Chief Scientist, Zoho
TechCrunch
26-05-2025
- Business
- TechCrunch
Vote for the sessions you want to see at Disrupt 2025
We were thrilled by the remarkable interest in speaking at TechCrunch Disrupt 2025, taking place October 27–29 at Moscone West in San Francisco. After an in-depth review process, we've selected 20 exceptional finalists—10 for breakout sessions and 10 for roundtables. Now, we're putting the final decision in your hands. Audience Choice voting is open through May 30 at 11:59 p.m. PT. You can vote for as many sessions as you'd like — one vote per session. The top 5 breakout sessions and top 5 roundtable sessions will be selected to take the stage. Meet the finalists Breakout Sessions How to Get Acquired in Tech (Without Selling Out): M&A Tips for Founders and Builders Aklil Ibssa, Head of Corporate Development and M&A, Coinbase Agentic AI for Startups: Automate, Adapt, and Accelerate Growth Anmol Rastogi, Head of Product, Amazon Business – AI & ML, Amazon Automation with Agents: From Work Enablement to Work Completion Chet Kapoor, Chairman and CEO, DataStax AI at the Brink: Strategic Playbook for National Security Dan Hendrycks, Executive and Research Director, Center for AI Safety (CAIS) Techcrunch event Join us at TechCrunch Sessions: AI Secure your spot for our leading AI industry event with speakers from OpenAI, Anthropic, and Cohere. For a limited time, tickets are just $292 for an entire day of expert talks, workshops, and potent networking. Exhibit at TechCrunch Sessions: AI Secure your spot at TC Sessions: AI and show 1,200+ decision-makers what you've built — without the big spend. Available through May 9 or while tables last. Berkeley, CA | REGISTER NOW Leading a Series A Round in 2025 and Sustaining Momentum Gabriel Kra, Managing Director, Prelude Ventures The Agentic Apocalypse: Securing the Enterprise in the Age of 1 Billion AI Agents Jack Hidary, CEO, SandboxAQ Jim Breyer, Founder and CEO, Breyer Capital Embracing AI for a Better Digital Future Matt Madrigal, Chief Technology Officer, Pinterest Mining for Millions with GenAI's 4 Ds: Striking Trust, Delight, and Dividends Michael Stewart, Managing Partner, M12 From Data to Agents: Building the AI-Native Enterprise Sridhar Ramaswamy, Chief Executive Officer, Snowflake From Vibes to Velocity: How AI Tools Can Help You Achieve Your Development Goals Tim Rogers, Staff Product Manager, GitHub Copilot, GitHub Roundtable Sessions Future of Space Economy in the Low Earth Orbit Abhijeet Kumar, Invited Lecturer – New Space Economy, UC Berkeley | Tech and Strategy Lead, Archer From Startup to Scale-Up: A GTM Blueprint Anjai Lal, Head of Strategy and Enablement, Google Cloud From Code to Capital: How VCs Spot the Next AI Powerhouses Avi Bharadwaj, Investment Director, Intel Capital The Winning Formula: Turning Your Business Into a Trusted, Scalable Community To Drive Growth Justine Palefsky and Tasneem Amina, Co-founders, Kindred Vlad Loktev, Partner, Index Ventures How to Train Your Model: Taming AI Agents Without Breaking Them Kyla Guru, Head of Model Cyber Policy, Anthropic Alex Moix, Investigations Lead, Safeguards, Anthropic Going a Layer Deeper: Why the future of AI investments lies with infrastructure and applications Paul Drews, Managing Partner, Salesforce Ventures Scaling Search and AI for Millions: Lessons from Reddit Search Rachel Miller, Product Manager, Reddit AI Evaluation 101: Addressing Challenges to Real-World AI Applications Rohit Patel, Director, Generative AI, Meta From Workarounds to Breakthroughs: How UpLink Lets Users Connect Any App—No Integration Needed Scott Weinert, CTO and Co-founder, Atomic Whose Company Is It, Anyway?: What You Lose When You Accept Outside Capital Sridhar Vembu, Chief Scientist, Zoho
Forbes
15-05-2025
- Business
- Forbes
Has IBM's IT Automation Software Gotten Better?
IBM Instana dashboard IBM There are two ways to answer the question posed in the headline. The simple answer is yes, IBM has continued to invest in acquisitions including HashiCorp and DataStax, leading to a more robust portfolio of products for enterprise IT shops. But, after attending IBM's Think conference in 2024, I walked away with concerns about this emerging portfolio of software. In particular, it seemed that IBM was struggling to develop an integrated product and go-to-market strategy. I was left scratching my head in terms of what advice I could give customers on how to engage with IBM and get some joint value out of these related but different solutions. Heading into last week's Think 2025, I wanted to be convinced that things were different despite more acquisitions. For the most part, I got what I was hoping for. (Note: IBM is an advisory client of my firm, Moor Insights & Strategy.) Last year I didn't think that IBM's software wasn't good or that it was lacking features. My concern was that IBM did not have a clear message about what made a number of point-products better together. For example, why would a longtime Apptio (IBM) customer consider switching to Instana (IBM) when they were perfectly happy with Instana competitor Dynatrace? Additionally, at Think last year IBM announced a new product called Concert that sounded kind of like Instana in some ways. So even if I did not already use a competing product, which IBM product should I buy? This year was quite different, and IBM was very clear about what it needed to change and what it ended up doing. I walked away from Think 2025 feeling much better than the previous year. But, I also think that for anyone evaluating IBM's IT Automation software, all factors need to be considered. Three of these stand out to me. As I stated earlier, I feel that a year has made a big difference in IBM's IT Automation software. And I think IBM gets what it needs to do to attract and satisfy customers. There were many more demos this year. The conversations were frank about how customers are using the technology in the real world. And I heard quite a bit about how much IBM has learned from these acquisitions, suggesting (I hope) that newer acquisitions may go smoother. On that front, I'm excited to see where we stand in another year with HashiCorp — which I'll be writing more about soon.
Techday NZ
07-05-2025
- Business
- Techday NZ
Ground truth: the critical step bridging GenAI prototypes and production-ready applications
It's never been easier to build a generative AI (GenAI) application. Today's developer tools, open-source frameworks and pre-trained models mean anyone can spin up a proof of concept in days. But taking that proof of concept and making it reliable, scalable and compliant enough to put into production? That's the real challenge. For Australian businesses and start-ups building in the GenAI space, grounding large language models (LLMs) in verifiable data is becoming the key to closing this gap. At DataStax, we've seen a recurring problem: many early-stage GenAI projects stall when it comes time to productionise. These applications often produce plausible but inaccurate results – a phenomenon commonly known as hallucination. While hallucinations might be tolerable in a lab, they're unacceptable in the real world where accuracy, compliance and trust are non-negotiable. Grounding is the process of aligning an LLM's outputs with factual, contextual and domain-specific data. Rather than relying solely on public training datasets, which may be outdated or irrelevant, grounding ensures that the model's responses can be verified against a company's internal knowledge base. This is essential when GenAI is being used in critical areas like customer service, healthcare, finance or law – any domain where mistakes come at a cost. In practical terms, grounding starts with a ground truth dataset – a curated collection of inputs and validated outputs that represent the "gold standard" for your application. This dataset serves as both a benchmark to evaluate your model's responses and a foundation for continuous improvement. It's the only reliable way to know whether your model is producing accurate, relevant and compliant information. Traditionally, creating this kind of dataset meant long hours from subject matter experts manually labelling inputs and verifying outputs. This doesn't scale well – especially for start-ups juggling rapid growth and limited resources. Some teams turn to crowdsourcing to accelerate the process, but that can introduce quality issues if the contributors lack domain knowledge. That's why automated approaches are now gaining traction. By using LLMs themselves to help generate and validate ground truth data – under human supervision – developers can dramatically reduce the time and cost required to build robust datasets. These methods also enable regular updates to the dataset, ensuring that applications evolve with changing regulations, product information and customer expectations. A grounded GenAI application is more than just a cool demo – it's one that organisations can trust. It performs reliably across edge cases, respects business rules and regulatory requirements, and provides responses that reflect the specific needs and language of the enterprise. This builds user trust, reduces operational risk, and opens the door for AI to take on more meaningful roles in business-critical workflows. Australian start-ups don't need to wait for these kinds of mistakes to learn the lesson. Ground truth is no longer optional – it's foundational. And with the right tools and processes, it's well within reach. DataStax's Hilton Rosenfeld, Data Architect and Krishnan Narayana Swamy, Principal Solution Engineer hosting a Mastering Agentic AI Workshop in Sydney on 7 May and Melbourne on 8 May. You'll learn how to: Implement RAG for precise FAQ handling. Build multi-agent systems to manage complex queries. Query customer orders and retrieve real-time product info using Astra DB. Deploy your own AI-powered support chatbot with a Streamlit front end. This free workshop is tailored for professionals and GenAI enthusiasts who want to build scalable AI applications that actually work in production. Bring your laptop and discover how to build a real-world customer support assistant using retrieval-augmented generation (RAG), Langflow, and Astra DB. Seats are limited, so reserve your spot and level up your GenAI capabilities. About DataStax DataStax is the company that helps developers and companies successfully create a bold new world through GenAI. We offer a one-stop generative AI stack with everything needed for a faster, easier, path to production for relevant and responsive GenAI applications. DataStax delivers a RAG-first developer experience, with first-class integrations into leading AI ecosystem partners, so we work with developers' existing stacks of choice. With DataStax, anyone can quickly build smart, high-growth AI applications at unlimited scale, on any cloud. Hundreds of the world's leading enterprises, including Audi, Bud Financial, Capital One, Skypoint, and many more rely on DataStax.
Yahoo
28-02-2025
- Business
- Yahoo
IBM to acquire DataStax; terms not disclosed
IBM (IBM) announced its intent to acquire DataStax, an AI and data solution provider. DataStax's technology will enhance IBM's watsonx portfolio of products accelerating the use of generative AI, helping companies unlock value from vast amounts of unstructured data, IBM said. Financial details of the transaction were not disclosed. The acquisition is expected to close in the second quarter of 2025, subject to customary closing conditions and regulatory approvals. See what stocks are receiving Strong Buy ratings from top-rated analysts. Filter, analyze, and streamline your search for investment opportunities with TipRanks' Stock Screener. Published first on TheFly – the ultimate source for real-time, market-moving breaking financial news. Try Now>> See the top stocks recommended by analysts >> Read More on IBM: IBM announces new agreement with Riyadh Air Quantum Computing News: Microsoft Unveils Majorana 1, Sparking Market Excitement IonQ Achieves Breakthrough in Making Compact Quantum Systems Quantum Watch: 3 Quantum Computing Startups Set to Disrupt the Industry Is Rigetti Computing's (RGTI) Upside Potential Worth the Wild Ride? Sign in to access your portfolio
