AI IMPACT: Taming Your AI Unit Economics with WEKA

Visa’s $3.5B Bet on AI

Visa’s SVP of Data & AI, Sam Hamilton, joins VentureBeat to break down the hidden costs, trade-offs, and infrastructure realities behind running over 400 AI solutions incorporating 300 AI models at global scale.

VB Transform 2025 Opening Remarks

Matt Marshall sets up this year's VB Transform 2025 event and kicks of the conversations.

Beyond Chatbots: The Shift to AI Agents in Customer Support

The evolution from traditional chatbots to AI-powered agents is revolutionizing customer support. While chatbots rely on scripted responses and predefined workflows, AI agents leverage advanced reasoning, automation, and personalization to handle customer inquiries, take actions on behalf of users, and continuously improve through learning. However, making this shift requires more than just upgrading technology — it demands a strategic rethinking of data integration, model training, and trust-building. In this VB Spotlight, we’ll explore the critical components of agentic AI in customer support and the key steps enterprises must take to transition successfully, from optimizing knowledge bases to ensuring seamless human-AI collaboration - and the benefits companies can realize from making this transition.

Live from GTC 2024 - Interview with Supermicro

Live from Nvidia’s GTC 2024: VentureBeat editor-in-chief Matt Marshall interviews Vik Malyala, Supermicro’s Managing Director & President, EMEA; SVP Technology & AI.

Will The Cost of Scaling Infrastructures Limit AI’s Potential?

AI delivers innovation at a rate and pace the world has never experienced, but the resources required to store and compute data in the age of AI will vastly exceed availability if limited to conventional technologies. The race is on to scale AI workloads while controlling infrastructure costs. Both conventional infrastructure providers and an emerging wave of alternative infrastructure providers are actively pursuing efforts to increase the performance of processing AI workloads while reducing costs, energy consumption, and the environmental impact to meet the rapidly growing needs of enterprises scaling AI workloads. Alternative technologies in development include quantum computing, DNA computational platforms, and photonic computing.