Targeting AI

In this special breaking news analysis edition of the Targeting AI podcast from AI Business, hosts Shaun Sutner and Esther Shittu dive into the latest developments in the AI industry with Torsten Volk, an analyst with Omdia. Both AI Business and Omdia are owned by Informa TechTarget. This episode covers AI cloud computing vendor CoreWeave's groundbreaking $14 billion AI compute deal with Meta Platforms, exploring its implications for enterprise AI and the future of data center services. Join us as we unravel the complexities of AI infrastructure, the race for GPU power, and the strategic moves shaping the tech landscape. Don't miss this discussion on the forces driving innovation and competition in AI. 
Takeaways:
CoreWeave's partnership with Meta underscores the growing need for specialized AI infrastructure.
Efficient GPU utilization is crucial for AI companies to maintain competitiveness.
The AI sector is rapidly evolving, with significant investments in infrastructure and talent.
Meta's strategy involves collaborating with various vendors to enhance its AI capabilities.
The deal may signal the emergence of a new sector within the AI industry, focusing on data center services.
 

As one of the biggest financial institutions in the U.S., Capital One isn’t running away from generative AI and agentic AI. Instead, the $490 billion company is using the technology to enhance both internal operations and customer experience. In this Targeting AI episode, the chief scientist and executive vice president at Capital One discusses some of the challenges and opportunities the financial giant is facing in customizing LLMs, and how the company continues to prioritize risk management and safety.
Featuring: Prem Natarajan, executive vice president, head of enterprise AI and chief scientist, Capital One
In today's episode, we cover:
Capital One's enterprise AI strategy is focused on creating customizable platforms using open source or open weight models
Capital One uses its proprietary data to customize AI models
The company uses GenAI and agentic AI for internal operations, such as with agent assist tools for customer service and customer-facing experiences like chat concierge
The enterprise has a focus on long-term transformation and not short-term ROI
To learn more about AI, open source and agentic AI, check out AI Business and SearchEnterpriseAI from Informa TechTarget.
To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech.
References:
Capital One AI partnerships aim to build trust and grow talent
Compare proprietary vs. open source for enterprise AI
The importance and limitations of open source AI models

As a legacy organization, IBM has long been a champion for open source, especially in the age of GenAI. In this episode of Targeting AI from Informa TechTarget, Bruno Aziza, vice president of data, AI and analytics at IBM, discusses how the vendor has had to rebrand and shift in the age of GenAI and agentic AI. Aziza shares insights on talent challenges, IBM's data strategy with Watson X, and the significance of customer-centric AI solutions. 
Featuring: Bruno Aziza, vice president of data, AI and analytics at IBM 
In today’s episode, we cover how: 
The shift to agentic AI is crucial for modern enterprises. 
Open source plays a vital role in AI development. 
IBM focuses on enterprise AI, rather than consumer-facing solutions. 
Talent scarcity is a significant challenge in AI innovation. 
99% of enterprise data remains untouched by AI. 
To learn more about AI, open source, agentic AI, check out SearchEnterpriseAI. 
To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. 
References: 
IBM customers assess the performance of AI agents 
IBM to buy open source data platform and AI vendor DataStax 
IBM targets agentic AI orchestration 

When it comes to diversity, AI systems often fail. In this episode of the Targeting AI podcast, Christina Mancini, CEO of Black Girls Code, discusses the importance of inclusion in tech, the strategies Black Girls Code employs to empower girls of color, and the need for ethical considerations in AI education. Christina emphasizes the role of communities of color as creators in AI and the necessity for equitable development in technology. She also outlines the future goals of Black Girls Code and how organizations can support their mission.
Featuring: Christina Mancini, CEO of Black Girls Code
In today’s episode, we cover:
Communities of color are often super users of technology but need to be creators too.
AI technologies must be built by diverse teams to avoid bias.
Organizations should pause to consider the impact of their products on all communities.
Collaboration with tech partners is essential for achieving their mission.
To learn more about AI, bias and diversity check out SearchEnterpriseAI.
To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech.
References:
Generative AI will force diversity in AI systems
Federal report focuses on AI diversity and ethics
Diverse data, ethical use key to responsible AI engineering

In a market dominated by Nvidia H100 GPUs, Cerebras Systems seeks to develop the world's largest AI chip, the Wafer Scale Engine. In this episode of Targeting AI from Informa TechTarget, James Wang, the vendor's director of product marketing, discusses the importance of the inference market for AI technology and how the company's strategic partnerships are essential for growth. He elaborates on the evolving landscape of AI, including the significance of agentic AI and touches on Cerebras' future direction as a cloud and API company.
Featuring: James Wang, director of product marketing at Cerebras Systems
In this episode, we cover how:
Cerebras approaches competing against Nvidia.
Cerebras approaches differentiating itself from other AI inference vendors
The company is evolving into a cloud and API product company to meet market demands.
Agentic AI represents a new frontier in AI applications, enabling complex tasks through multiple requests.
To learn more about AI and Cerebras Systems and other hardware news, check out SearchEnterpriseAI. 
To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. 
References: 
Cerebras launches Alibaba model, forms key AI partnerships
Cerebras' inference AI tool challenges Nvidia, but faces hurdles
Microsoft, AWS and Cerebras launch DeepSeek-R1 model
 

In this two-year anniversary episode of Targeting AI from Informa TechTarget, Michael Bennett discusses the rapid evolution of generative AI technology, and its implications for society, legal frameworks and creative industries. He highlights the public's growing awareness and understanding of AI, the legal challenges surrounding copyright and fair use, and the moral questions that arise from the use of AI in creative fields. 
Featuring: Michael Bennett, associate vice chancellor for data science and artificial intelligence strategy at University of Illinois Chicago 
In this episode, we cover: 
The public's awareness of AI technology has significantly increased since the release of ChatGPT. 
Legal challenges surrounding generative AI focus on copyright and fair use, creating uncertainty for the industry. 
The disparity in AI infrastructure may lead to unequal benefits and negative consequences globally. 
The future of AI, including AGI (artificial general intelligence), is uncertain and requires careful consideration. 
To learn more about AI and the other regulation and governance news, check out SearchEnterpriseAI. 
To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. 
References: 
AI regulation: What businesses need to know in 2025 
XAI releases Grok 4 amid furor over antisemitic comments 
Anthropic’s early lawsuit win pushes courts forward on fair use 

In this special news edition of Targeting AI from Informa TechTarget, government reporter Makenzie Holland discusses President Trump's AI action plan and executive orders aimed at promoting AI development and ensuring U.S. dominance in the AI race.
Featuring: Makenzie Holland, Informa TechTarget senior news writer
In today’s episode, senior new director Shaun Sutner and AI news writer Esther Shittu cover these topics:
President Trump’s new executive order and its intent
How the executive orders differ from the president’s previous orders and President Biden’s 2023 executive order
Woke AI and political bias concerns
To learn more about AI and the other regulation and governance news, check out SearchEnterprise AI and SearchCIO
To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech.
References:
White House AI plan places scrutiny on state AI laws
Senate’s ‘One Big, Beautiful Bill’ affects AI, U.S. energy
S. policy moves reflect big tech issues with state AI laws
 

In this episode of the Targeting AI podcast from Informa TechTarget, Ben Flast, of NoSQL database vendor MongoDB, discusses the company's rapid integration of generative AI technologies, including vector search and real-time updates through Atlas Stream Processing. He emphasizes the importance of community engagement and the role of agentic AI in enhancing developer productivity. The conversation also explores the differences between open source and proprietary models, the impact of model sizes on performance, and MongoDB's approach to AI governance. Flast shares customer applications that highlight the transformative potential of AI in various industries and concludes with insights into future innovations at MongoDB.
Featuring: Ben Flast, director of product management at MongoDB
In today's episode, we cover these topics:
Vector search enhances the capabilities of GenAI applications.
Agentic AI represents a new application pattern for AI capabilities.
Model size affects performance and cost for developers.
To learn more about AI and the importance of GenAI in database platforms, check out SearchEnterprise AI and SearchDataManagement.
To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech.
References:
Atlas Stream Processing
MongoDB vector search
Model Context Protocol GenAI standard

The lack of diversity in AI systems has been an issue since the birth of the technology. In this episode of the Targeting AI podcast from Informa TechTarget, Karen Panetta discusses the importance of diversity in tech, and the ethical implications of AI. She emphasizes the need for inclusive design in engineering and AI systems, the role of digital twins in education, and the challenges of AI bias.
Featuring: Karen Panetta, an IEEE fellow and dean of graduate engineering education at Tufts University
In today's episode, we cover these topics:
AI should focus on solving real-world problems rather than being applied indiscriminately.
Ethical AI must prioritize the principle of “do no harm” to individuals and communities.
AI bias can lead to significant real-world consequences, especially in healthcare and hiring.
and more.
To learn more about AI and the importance of diversity in AI systems, check out SearchEnterprise AI.
To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech.
References:
Generative AI will force diversity in AI systems
Federal report focuses on AI diversity and ethics
Diversity in hiring a key to eradicating AI bias
 

In this episode of the Targeting AI podcast, Shaun Sutner and Esther Ajao interview Alan Trefler, founder and CEO of Pegasystems, discussing the evolution of AI technology, particularly generative AI, and its integration into business processes. Trefler shares insights on the differences between design time and runtime applications of AI, the importance of workflow engines, and the challenges of AI safety and reliability. He emphasizes the need for collaboration between AI and human expertise, and outlines Pegasystems' roadmap for effectively using AI in business process automation and legacy transformation.
Featuring: Alan Trefler, founder and CEO, Pegasystems.
In today's episode, we cover how:
GenAI has significantly advanced Pegasystems' offerings.
GenAI coaches differ from traditional generative AI assistants by focusing on design time.
Design time is crucial for ensuring reliable AI outcomes in business settings.
GenAI can enhance business process automation by streamlining workflows.
References:
Pegasystems expands agentic AI for business automation | TechTarget
Pegasystems expands generative AI in CX, BPA cloud platform | TechTarget
Pegasystems unveils AI assistant for knowledge management | TechTarget
CRM and BPM vendor Pegasystems adds new AI features | TechTarget
To learn more about AI and Pegasystems, check out Informa TechTarget news sites, including SearchCustomerExperience and SeachEnterpriseAI
To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech.