Targeting AI

Epizode

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  Shutterstock, AI image licensing and the future of human-led content 11.08.2026 35min

  The explosion of AI in 2022 coincided with the introduction of image-generating models such as Dall-E, which were met with controversy. However, in recent years, AI companies have partnered with legacy image vendors such as Getty Images and Shutterstock. On this episode of Targeting AI, Daniel Mandell of Shutterstock explains how data licensing is changing in the age of generative AI. Mandell explains how Shutterstock has evolved from a stock content company into a data licensing partner for model training, inference and increasingly agentic workflows. We discuss how Shutterstock approaches creator compensation, how it filters synthetic data, why inference is becoming as important as training, and why high-quality rights-cleared content still matters even as image generators improve. Featuring: Daniel Mandell, senior vice president of data licensing and AI at Shutterstock In this episode, we cover how: Shutterstock’s AI business grew from image licensing into a broader multimodal data licensing model covering video, audio, 3D, fonts and templates. The company now serves both model training and inference use cases, with inference becoming a major part of the business. Demand has shifted from broad volume requests to highly specific, niche, and metadata-rich content for real-world applications. Mandell says Shutterstock is not trying to be a model builder, but rather a content and data partner that helps customers solve practical AI problems. The company sees its role as combining stock assets with AI-generated content to offer more optionality to customers. Compensation for creators remains an open challenge, but Shutterstock says it is trying to ensure contributors stay part of the AI ecosystem and continue to monetize their work. Synthetic data is useful for edge cases, but Mandell argues models still need real rights-cleared human-made data to perform well. To learn more about AI and finance, 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: And Now it Begins: Shutterstock Unveils Text-to-Image AI Platform The need for tools such as Getty Generative AI by iStock The Perplexity-Getty Images Licensing Deal is Different
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  How F2's AI Platform Transforms Private Credit and Equity 28.07.2026 41min

  In this episode, Don Muir of AI-native private market investment platform vendor F2, discusses how AI is transforming private markets investing by automating data processing, standardizing unstructured data, and building a system of agentic workflows tailored for financial institutions. He explains the importance of AI native solutions for private credit and equity, and how F2's platform helps decision-making and operational efficiency. Featuring: Dan Muir, co-founder and CEO of F2 In this episode, we cover: AI's role in automating private market workflows Standardization of unstructured financial data Agentic AI systems tailored for finance Impact of AI on private credit and equity markets F2's platform and its customization for firms Balancing probabilistic AI with deterministic financial data Pricing models for AI-driven financial services Future growth and market convergence in private markets AI's role in risk management during market dislocation To learn more about AI and finance, 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: Native AI on Horizon for Finance, Accounting Teams Robinhood Will Let Agents Trade -- It Could Be a Trend Global study reveals biggest risks of AI in finance sector
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  Building the AI-Powered Enterprise: Strategies for Agentic AI Adoption 14.07.2026 28min

  With agentic AI and generative AI, enterprises are continually looking for ways to transform their workflows. In this episode of the Targeting AI podcast from AI Business, Esther Shittu and Shaun Sutner welcome Jason Olkowski of CRM and workforce automation vendor Creatio, to examine how enterprises can use agentic AI to improve decision-making within their workflows and unlock true value. Featuring: Jason Olkowski, chief strategy officer at Creatio In this episode, we cover: Enterprise AI adoption gaps and organizational maturity The concept of the unlimited enterprise and removing platform limits Creatio's new AI agents for banking and their governance frameworks Prioritizing AI initiatives for business impact The role of AI in decision-making and worker augmentation To learn more about using agentic AI in enterprise workflows, 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: How Creatio is Redefining CRM for Financial Institutions Turning Agentic AI From Idea to Essential Enterprise Process Nvidia Launches Workflows for Organizations to Build Their Own AI  
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  Exploring AI Adoption and Safety for SMBs 30.06.2026 44min

  In this episode of the Targeting AI podcast from AI Business, Shaun Sutner and Esther Shittu host Ben Schreiner from AWS to discuss the evolving landscape of AI adoption among small and medium-sized businesses (SMBs). They delve into AI safety, AI adoption by SMBs, practical use cases, choosing the right partners, managing costs, and the future of AI tools tailored for SMBs -- emphasizing responsible deployment, the importance of trust in data, and how AI can augment human effort rather than replace it. Featuring: Ben Schreiner, head of AI and modern data strategy business development at AWS In this episode, we cover: AI adoption challenges for SMBs AI safety and guardrails Partner selection and vendor lock-in AI tools and real-world SMB applications To learn more about AWS and AI for enterprises and SMBS, 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: AWS Launches Frontier Agents AWS Simplifies Agent Building With Model Customization How AI Can Lead to Operational Transformation in Smaller US Companies
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  Rebellions vs. Nvidia: The Inference Chip Revolution 16.06.2026 28min

  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
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  How humans and AI can co-exist productively in the workplace 02.06.2026 35min

  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  
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  Real-Time Intelligence in the Age of Generative AI: Insights from Dataminr 19.05.2026 32min

  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
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  LinkedIn’s Change to its Search Engine Could Affect Your Job Search 05.05.2026 46min

  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
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  AI PCs and chips: Their role in the enterprise 21.04.2026 27min

  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  
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  The Agentic AI Foundation and Linux Foundation on agentic AI 07.04.2026 26min

  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    
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  AI Co-Workers and the Future of Work 24.03.2026 27min

  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
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  Understanding Human Impact and Safety in AI 10.03.2026 28min

  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      
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  How Capital One is building an AI-ready data ecosystem with creative talent 09.03.2026 19min

  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            
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  Navigating the generative AI landscape with two MIT profs 03.03.2026 37min

  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    
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  Coinbase, crypto, blockchain and the outlook for digital payments 17.02.2026 26min

  AI is changing digital payments, and Coinbase is trying to lead that change. Last year, the cryptocurrency exchange provider partnered with Cloudflare, AWS, Anthropic and others to create the x402 protocol, a standard that enables AI agents to make transactions online. In this conversation, Coinbase’s Dan Kim talks with Targeting AI hosts Esther Shittu and Shaun Sutner AI about how generative AI is critical in creating a new class of AI agents that can autonomously engage in trading and transactions.  Featuring: Dan Kim, vice president, head of digital asset listings & services at Coinbase In this episode, we cover: Coinbase's mission is economic freedom through cryptocurrency and blockchain. AI is transforming software to be more intelligent and adaptive. The X402 Foundation aims to standardize how payments are processed over the internet. AI agents are becoming a new class of customers in the trading space. Stablecoins are crucial for secure transactions between AI agents. To learn more about generative and agentic AI and RPA, 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: X402 Aims to Enable Agentic Payments with Digital Dollars Blockchain for businesses: The ultimate enterprise guide What is a Stablecoin?
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  The Future of AI in Process Intelligence 03.02.2026 26min

  In this episode of the Targeting AI podcast from AI Business, Manuel Haug, of Germany-based process mining vendor Celonis, discusses the intricacies of process mining and its integration with AI technologies. He explains how Celonis differentiates itself in the market, the evolution of its strategy in light of generative AI, and the practical applications of AI agents in various industries. Haug emphasizes the importance of operationalizing process mining findings and preparing for the future of work as the workforce ages. He also touches on the complementary nature of AI and traditional automation methods, such as RPA, and the need to capture organizational knowledge before it is lost. Featuring: Manuel Haug, field CTO of Celonis In this episode, we cover how: Process mining connects to various IT systems to analyze business processes. AI can improve and automate manual processes in companies. AI agents can assist human teams in decision-making. Operationalizing findings from process mining is crucial for improvement. The aging workforce necessitates capturing knowledge effectively. RPA and AI can coexist and complement each other in automation. Understanding processes is foundational for effective AI implementation. AI technology is becoming more reliable and powerful. The future of work will involve a blend of AI and human oversight. To learn more about generative and agentic AI and RPA, 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: 5 Benefits of Using Process Mining Process Mining Software Comparison: What CIOs Should Look at Top Enterprise Process Mining Challenges, Ways to Solve Them      
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  From Predictive to Agentic: The Future of AI in Sales 20.01.2026 28min

  If most sales representatives spend nearly a quarter of their time on administrative tasks, they are losing opportunities to generate revenue and be productive in sales. This is why Eilon Reshef of AI sales platform vendor Gong sees AI technology as a supportive co-worker that can offload menial admin tasks from sales agents so they can focus on their new jobs. He shares insights into Gong's mission to enhance sales team productivity and the importance of data in AI applications. Featuring: Eilon Reshef, co-founder and chief product officer, Gong In this episode, we cover how: AI's effectiveness is heavily dependent on the quality of data. "Gong" symbolizes success in sales. Agentic AI is about automating complex tasks intelligently. Sales roles are evolving, not disappearing, due to AI. The future of sales will involve more AI-driven insights. 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: AI and automation: Transforming sales CRM Phenom’s Acquisition: AI, Automation and the Future of Work Salesforce Launches AI Cloud to Bring Generative AI to the Enterprise
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  Google AI exec says data is the next phase of generative AI 06.01.2026 39min

  At the start of the mass popularity phase of generative AI, large language models were the star of the show. Vendors released bigger and newer models. However, the conversation has recently shifted from considering big or small models to a deep focus on data. In this episode of the Targeting AI podcast from AI Business, Yasmeen Ahmad, of Google Cloud, discusses the transformative effect of generative AI on the data landscape. She emphasizes the importance of treating data as a product, the shift toward multimodal data, and the role of AI agents in enhancing data management and decision-making processes. Featuring: Yasmeen Ahmad, managing director of product management for data and AI Cloud, Google Cloud In this episode, we cover how: The era of multimodal data is upon us, integrating various data types. Agentic AI enhances the understanding of unstructured data. Databases must evolve into cognitive reasoning engines for AI. Gemini Enterprise provides a unified platform for AI and data. Data security and responsibility are critical in AI deployment. To learn more about the role data plays in 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: Generative AI is the Future of Data Management Without Data There Is No AI Google Invests $40B in AI Data Centers in Texas
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  Vertical AI Systems and Open Source Flexibility 16.12.2025 20min

  Generative AI and agentic AI tools are only as good as the problem that they are used to solve. In some cases, using generic AI tools can help with non-specific issues. However, Raj Shukla, of enterprise AI platform vendor Symphony AI, says the future of AI technology will focus on vertical applications and open models. In this Targeting AI episode from AI Business, he emphasizes that open source models provide flexibility and the ability to fine-tune for specific use cases. Featuring: Raj Shukla, CTO, Symphony AI In this episode, we cover: Symphony's AI mission of bringing AI technology to legacy industries that may struggle with adoption. A vertical approach combines predictive, generative and agentic AI to address specific challenges. The move in vertical areas from a traditional rule-based approach to a more dynamic, non-deterministic tool. AI applications in these verticals can significantly improve operational efficiencies and strategic decision-making. To learn more about vertical AI applications, 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: Small Language Models Gaining Ground at Enterprises Vertical AI agents explained: The future of enterprise tech AI21 releases open source tiny language model
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  The Impact of the "One Rule" AI Executive Order 15.12.2025 5min

  President Donald Trump signed an executive order last week that looks to override AI state laws in favor of a national policy. Titled "Ensuring a National Policy Framework for Artificial Intelligence," it directs the Department of Justice to establish an AI Litigation Task Force and challenge "cumbersome" state laws. It also asks the Secretary of Commerce to consider withholding federal funds from states found to have restrictive AI laws. In this podcast, Michael Bennett discusses what the EO means for states like New York and California, which already have established laws in place, and how they might respond.  Featuring: Michael Bennett, Associate Vice Chancellor for Data Science and Artificial Intelligence Strategy, University of Illinois Chicago  In this episode, we cover how:  The EO aims to prevent conflicting state laws on AI.  States with existing AI regulations are likely prepared to resist the EO.  The U.S. has a more laissez-faire approach to AI regulation compared with the EU and China.  The order could lead to significant political battles leading up to the midterm elections.  The effectiveness of minimal regulation in winning the AI race is uncertain.  To learn more about AI regulations, check out AI Business, 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:  Navigating Big Tech’s Influence on the AI Regulatory Landscape in 2025  Big Tech Firms Ask for AI Regulation but Quietly Hedge Their Bets  US State Attorneys General Demand Greater AI Safety From Tech Giants