Targeting AI

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Jun 2026

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Hosts Shaun Sutner, TechTarget News senior news director, and AI news writer Esther Ajao interview AI experts from the tech vendor, analyst and consultant community, academia and the arts as well as AI technology users from enterprises and advocates for data privacy and responsible use of AI. Topics are related to news events in the AI world but the episodes are intended to have a longer, more ”evergreen” run and they are in-depth and somewhat long form, aiming for 45 minutes to an hour in duration. The podcast will occasionally host guests from inside TechTarget and its Enterprise Strategy Group and Xtelligent divisions as well and also include some news-oriented episodes featuring Sutner and Ajao reviewing the news.

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June 16, 2026Episode 8828 min

Rebellions vs. Nvidia: The Inference Chip Revolution

In this episode of the Targeting AI podcast from AI Business, Shaun Sutner and Esther Shittu interview Marshall Choy of Rebellions, a South Korea-based inference chipmaker. The conversation covers Rebellions' focus on AI inference, the company’s global expansion strategy, the importance of open source in its software stack, and its chiplet architecture. Choy discusses the competitive landscape dominated by giants like Nvidia, the K-Nvidia initiative, and the future of AI infrastructure, emphasizing the need for AI sovereignty and South Korea's role in the global AI market. Featuring: Marshall Choy, chief business officer at Rebellions In this episode, we cover: Rebellions’ aims to challenge Nvidia's dominance in the AI industry. The focus on inference allows for broader market opportunities. Global expansion is a key priority for Rebellions. Open source software is integral to the vendor’s strategy. Chiplet architecture provides flexibility and cost efficiency. The K-Nvidia initiative aims to strengthen South Korea's AI capabilities. AI sovereignty is becoming increasingly important for enterprises. The future of AI infrastructure is shifting toward reasoning capabilities. Rebellions’ goal to be a durable corporation in the tech landscape. To learn more about Rebellions and AI inference, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: South Korean AI Chipmaker Raises $400M for Inference South Korean Chipmaker Partners with SKT, Arm for Sovereign AI Neocloud Pioneer CoreWeave All in on Inference

June 2, 2026Episode 8735 min

How humans and AI can co-exist productively in the workplace

The future of work is humans and AI collaborating. Despite developments in which technology companies blame AI for the decision to lay off large numbers of workers, Nikhil Krishnan of C3 AI says there is still a need for a human in the loop. On the latest Targeting AI podcast from AI Business, Krishnan said the future of work will involve a pyramid-type system. At the bottom, the AI will automate certain processes, but at the middle and top levels, there should be collaboration between the human and AI. Featuring: Nikhil Krishnan, CTO at C3 AI In this episode, we discuss: The pyramid structure of the future of work The need for the human in the loop The industry that is currently not seeing AI replacing humans C3 AI’s differentiation from hyperscalers and competitors The AI boom versus bubble debate The importance of operational efficiency in any economic environment To learn more about C3 AI and the future of work, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: C3 AI Launches C3 Code for Businesses Seeking Domain Expertise Phenom’s Acquisition: AI, Automation and the Future of Work Fourth Industrial Revolution: How AI Agents Are Transforming the Future of Work

May 19, 2026Episode 8632 min

Real-Time Intelligence in the Age of Generative AI: Insights from Dataminr

For many organizations, the advent of AI has necessitated a transition from a human-centric to an intelligence- or even agentic-based approach. Real-time event, threat and risk vendor Dataminr began its transition to intelligent automation in 2018, marking the start of its AI journey. Since then, the vendor has transitioned to a more agentic and generative AI approach. In this interview, Joel Tetreault of Dataminr discusses the evolution of real time intelligence platforms, the integration of generative AI and agentic AI, and the importance of data strategy in AI development. Featuring: Joel Tetreault, chief AI officer, Dataminr In this episode, we discuss the: Evolution of Dataminr’s platform pre- and post-generative AI Integration of GPT and modern models in real-time data processing Role of data strategy and domain-specific models in AI effectiveness Use of multimodal AI for security and threat detection Impact of agentic AI and future trends in cybersecurity To learn more about AI search, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Top 10 Cybersecurity predictions for 2026 How to enhance OSINT investigations using AI Company Using AI to Strengthen Cybersecurity Raises $50M

May 5, 2026Episode 8546 min

LinkedIn’s Change to its Search Engine Could Affect Your Job Search

Most people looking for a job usually spend hours scouring job search engines and LinkedIn. However, the professional network has changed the way its search engine works, shifting from a keyword-based, taxonomy-driven system to an AI-powered semantic search that understands natural language. In this podcast episode, Caleb Johnson of LinkedIn dives into how LinkedIn uses AI and large language models (LLMs) to revolutionize job search, improve search relevance, and ensure data privacy. Featuring: Caleb Johnson, principal staff software engineer In this episode, we cover: AI-powered job search and semantic understanding Use of LLMs and transformer architecture Bias mitigation and fairness in AI systems Data privacy and compliance in AI applications Future directions: voice, visual search, and interactive AI To learn more about AI search, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Indeed Unveils AI Agents for Job Seekers and Recruiters Google's AI-Powered Chrome Further Transforms Search LinkedIn Unveils AI Updates for Business Users, Job Seekers

April 21, 2026Episode 8427 min

AI PCs and chips: Their role in the enterprise

With the rise of generative AI and agentic AI, there has also been a push for AI PCs within the enterprise. Companies like Lenovo and Microsoft are providing enterprises with devices that help create these devices. However, there is no AI PC without AI chips. In this podcast, Michael Nordquist of chipmaker AMD discusses the evolution of AI chips and AMD's role in the rapidly changing AI landscape. He highlights the features of AI PCs, the impact of AI on enterprise efficiency, and AMD's strategy against competitors such as Nvidia. Featuring: Michael Nordquist, corporate VP of product marketing, AMD In this episode, we cover: AMD's position as a key player in AI technology. How AI PCs integrate NPUs for enhanced performance. The need for vendors to focus on security when developing AI PCs. How adoption of AI PCs is influenced by perceived value. The future will see a blend of personal and enterprise AI agents. To learn more about AI PCs, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: AMD Competes With Intel With AI New Chips AI PCs Are Going Mainstream, Says AMD's Jason Banta Microsoft Aims for AI PCs While Apple Unveils M5 Chips

April 7, 2026Episode 8326 min

The Agentic AI Foundation and Linux Foundation on agentic AI

Agentic AI has grown rapidly in the past two years, and with that growth comes different tools that help agents work. Among those tools is the Model Context Protocol from Anthropic. In this episode of the Targeting AI podcast from AI Business, Jim Zemlin and Mazin Gilbert dive into the importance of agentic AI, the relevance of MCP, the nuances of openness in AI, and the responsibilities surrounding AI security and ethics. The conversation also touches on the future of personal agents and the evolving role of developers in the AI landscape, with the popularity of OpenClaw. This episode was recorded on-site in New York City last week at the MCP Developer Summit presented by the Agentic AI Foundation. Featuring: Jim Zemlin, CEO of the Linux Foundation, Mazin Gilbert, executive director of the Agentic AI Foundation In this episode, we cover how: Agentic AI is crucial for driving information exchange and financial transactions. Standardization is necessary as we move from experimentation to production in AI. The Linux Foundation provides a neutral space for collaboration among tech companies. Openness in AI includes varying degrees of access to data and models. Ethical AI usage is a priority for the AI industry to prevent bias. Developers' roles are shifting from coding to system architecture and security. The future of AI will involve both open and closed data. To learn more about Agentic AI, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: MCP is Alive, But Faces Challenges How to Prepare Supply Chains for Agentic AI The Growing Need for Cybersecurity in Agentic AI

March 24, 2026Episode 8227 min

AI Co-Workers and the Future of Work

The future of work is continuing to change with AI, and many agree that AI co-workers are becoming part of everyday work. However, many enterprises still find it challenging to understand the various use cases for AI, the role AI can play in enhancing productivity, and the need to approach AI implementation thoughtfully, focusing on real problems rather than succumbing to FOMO. In this conversation on the Targeting AI podcast from AI Business, HP's Faisal Masud shares insights on the future of work and HP's commitment to integrating AI into its offerings. Featuring: Faisal Masud, President, digital & lifecycle services, HP In this episode, we cover how: Consumers are more advanced in using AI than enterprises. AI at the edge enhances privacy and security. Enterprises need to understand specific use cases for AI. How HP approaches its differentiation strategy. ROI in AI projects should consider productivity and cost reduction. AI should augment human capabilities, not replace them. The future of work will involve AI as a co-worker. To learn more about AI adoption, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: HP's New Keyboard Gives New Meaning to All-in-One AI Innovation vs Adoption: Why They Are Misaligned Generative AI Adoption Grows Fivefold, Capgemini Reports

March 10, 2026Episode 8128 min

Understanding Human Impact and Safety in AI

In a special episode of the Targeting AI podcast from AI Business, host Esther Shittu interviews Christopher Campbell of Lenovo about the challenges and considerations surrounding AI governance, emphasizing the importance of human impact, safety, and accountability. They explore the evolving perspectives on bias and hallucinations in AI, the role of hardware in AI development, and the implications of personal AI agents. The discussion highlights the importance of selecting the right AI partners, maintaining governance in hybrid AI environments, and addressing the complexities of shadow AI and AI governance sovereignty. The episode concludes with advice for organizations on effectively adopting AI governance practices. The podcast was recorded on-site at the Gartner Data & Analytics Summit in Orlando. Featuring: Christopher Campbell, director of AI governance and global products and services security leader at Lenovo In this episode, we cover how: The human impact and safety of AI are paramount. Trust in AI systems is essential for their success. Bias and hallucination perspectives have matured over time. Accountability in AI governance lies with leadership. Choosing AI partners with aligned philosophies is crucial. Governance standards apply equally to local and cloud models. Shadow AI presents a complex challenge for organizations. Sovereignty in AI gives regions more control over their data. Understanding technology is key to effective AI adoption. There is no one-size-fits-all approach to AI governance. To learn more about AI governance, safety and sovereignty, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: AI data governance guidance that gets you to the finish line The AI bias playbook: Mitigation strategies for CIOs Major sovereign AI funding deals kick off India AI Impact summit

March 9, 2026Episode 8019 min

How Capital One is building an AI-ready data ecosystem with creative talent

In this interview on the Targeting AI podcast from AI Business, Amy Lenander of financial services giant Capital One discusses the critical role of talent in building AI-ready data ecosystems. She explores how organizations can cultivate the right skills, develop foundational data platforms and use AI to drive business value. The interview was recorded on-site at the Gartner Data & Analytics Summit 2026 in Orlando. Featuring Amy Lenander, chief data officer, Capital One In this episode, we cover how: Talent agility outweighs technical experience in AI success. Organizations that develop learning agility and curiosity foster talent capable of navigating rapidly evolving AI landscapes. Instead of hiring for a specific toolset, focus on candidates who demonstrate rapid learning, problem-solving, and collaboration—traits that enable mastery of new AI methods as they emerge. Building a unified data ecosystem creates a competitive moat. A well-designed data ecosystem, prioritized over immediate AI application, provides a robust foundation that supports all future data and AI initiatives. Investing in governance, data trustworthiness, and accessibility shields organizations from fragmentation, enabling scalable innovation regardless of future technological shifts. AI adoption is a cultural shift, not just a technology implementation. Domain-specific data products enhance AI interpretability and trust. Specialized data teams responsible for understanding business nuances ensure AI systems interpret data context correctly for strategic use. To learn more about generative and agentic AI and AI-ready data ecosystems, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: The Shift Toward AI Data Quality as a Core Product Data Quality in AI: 9 Common Issues and Best Practices Data and AI Governance Must Team Up for AI to Succeed

March 3, 2026Episode 7937 min

Navigating the generative AI landscape with two MIT profs

In this episode of the Targeting AI podcast from AI Business, hosts Shaun Sutner and Esther Shittu engage with Abel Sanchez and John Williams from MIT to discuss the evolving landscape of generative AI. The conversation covers the motivation behind their initiative, Gen AI Global, the dynamics of their professional relationship, and the societal implications of AI technologies. They explore concepts such as "vibe living," the energy demands of AI, and contrasting perspectives on AI's future, including the debate between optimists and skeptics. The episode concludes with a discussion on the sustainability of the AI boom and the importance of human involvement in an increasingly automated world. Featuring: Abel Sanchez, a research scientist and executive director of MIT's Geospatial Data Center; and John Williams, professor of civil and environmental engineering at MIT and director of the Geospatial Data Center and Intelligent Engineering Systems laboratory at MIT. In this episode, we cover how: Learning is social; community enhances educational outcomes. Generative AI is rapidly changing industries and education. AI's impact on society is both exciting and concerning. The relationship between Abel and John is built on trust and differing perspectives. Generative AI can empower non-experts to achieve expert-level results. Energy consumption for AI is a growing concern. The future of AI models may involve new architectures beyond transformers. Human intuition and emotion remain valuable in AI applications. The AI boom is characterized by rapid adoption and innovation. Organizations must adapt to integrate AI effectively. To learn more about generative AI, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Gen AI Global How much energy do data centers consume? Debate Rages Over AI Bubble vs. Boom