Targeting AI

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.

Nvidia's hardware strategies are powering AI technologies. Recently, networking has become the critical backbone of modern AI systems. In today’s episode, Kevin Deierling provides practical insights for enterprises looking to implement AI technologies effectively. Deierling contrasts traditional data centers with the emerging concept of AI factories, revealing how these specialized environments are reshaping enterprise computing. Featuring: Kevin Deierling, senior vice president of networking, Nvidia. In today's episode, we cover: Nvidia hardware and software approach AI factories and data centers Agentic AI and the shift toward complex reasoning and more. To learn more about AI and Nvidia, check out SearchEnterprise AI. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Nvidia AI platform for cloud GPU providers widens supply Nvidia, AMD and others tout partnership with Saudi Arabia Nvidia aims at agents, physical AI with reasoning models

Generative AI has led to many fears about the workforce. However, for work management platform vendor Asana, GenAI and agentic AI can be effective tools in the workforce. Instead of replacing humans, AI technology can work alongside humans. Despite the potential for collaboration, not all tasks require the use of AI technology. Featuring: Saket Srivastava, CIO of work management platform, Asana. In today's episode, we cover: The collaboration between AI technology and humans Employees need training and support in AI How GenAI can significantly improve project management tasks and more. To learn more about AI and Asana, check out SearchEnterpriseAI. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Project management vendor Asana brings AI to Work Graph 6 of the top change management applications Connected workspace apps improve collaboration management

As an AI writing assistant, Grammarly has used AI technology from its inception. The popularity of large language models has led to a shift in which the writing assistant vendor moved from natural language processing to including large language models to help enterprise employees improve their writing as they work. This has led Grammarly to see a possibility in the part it can play in transforming the future of work. Featuring: Luke Behnke, head of Enterprise Product at Grammarly, an AI-powered assistant writing platform. In today’s episode, we cover: Grammarly’s AI evolution Agentic AI and the future of work AI technology as an assistant and not a replacement for work and more. To learn more about AI and Grammarly, check out SearchEnterprise AI. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Grammarly AI and an update to the writing tool What will be the future of the workplace? Top 4 AI writing tools for improved business efficiency

A key truth about AI is that regulation has long lagged innovation. However, this has not removed the responsibility of enterprises to deploy AI systems responsibly or for AI vendors to create responsible systems. What are the key metrics to understanding a safe AI system? Featuring: Stuart Battersby, CTO at Chatterbox Labs, vendor of a quantitative AI risk metrics platform, and Danny Coleman, CEO at Chatterbox. In today’s episode, we cover: The difference between AI safety and responsible AI The need for standards in AI safety The future of AI safety in Enterprises and more. To learn more about responsible AI, check out SearchEnterprise AI. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Assessing if DeepSeek is safe to use in the enterprise EU, U.S. at odds on AI safety regulations Responsible AI vs. ethical AI: What's the difference?

Industrial AI is less familiar than consumer AI, but represents a critical and growing sector within AI’s influence. What unique AI applications are surfacing in this area? Featuring: Olympia Brikis, director of Industrial AI research at Siemens In today’s episode, we’ll cover… Understanding Industrial AI and its distinctions from consumer AI AI and, specifically, generative AI adoption at Siemens The role of digital twins in testing AI recommendations and more. To learn more about AI in healthcare, check out Search Enterprise AI. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: CES 2024: Siemens eyes up immersive tech, AI to enable industrial metaverse How businesses are using AI in the construction industry Siemens forges digital twin deal with Nvidia for metaverse

In this discussion, Deepak Singh, Vice President at AWS with extensive experience in open source and developer tools, shares his insights on the evolution of AI. He highlights the distinctions between traditional, generative, and agentic AI, emphasizing how agentic AI automates routine tasks in software development. The talk delves into the importance of high-quality data for enhancing AI performance and AWS's innovative platforms like SageMaker and Bedrock, which drive advancements in creating high-performing autonomous AI agents.

In the couple of years since the popularization of ChatGPT, generative AI technology has quickly taken hold in the legal profession. It has backfired in some cases, such as when an attorney filed a legal brief written with ChatGPT's help and the AI platform hallucinated some of the cases in the brief. That case and others have led some law firms to block general access to AI tools. Most recently, Hill Dickinson, a law firm in the U.K., asked its staff not to use generative AI tools like ChatGPT. Many law firms are using generative AI tools, and some even market their own AI systems. AI vendors are also partnering with law firms and companies in the legal profession. In February, LexisNexis and OpenAI agreed to integrate OpenAI's large language models across its products. The success, and uncertainty, surrounding AI tools in the legal profession led James M. Cooper and Kashyap Kompella to write the book A Short and Happy Guide for Artificial Intelligence for Lawyers. Cooper is a law professor at California Western School of Law, while Kompella is CEO of AI analyst firm RPA2AI Research. In the book, Cooper and Kompella explore how lawyers can understand and use AI technology. "We saw an urgent need to upskill lawyers on AI," Kompella said on the latest episode of Informa TechTarget's Targeting AI podcast. "How do you move AI ethics and responsible AI into practice? You have to move them through lawyers. Lawyers are a big part of that equation." Kompella and Cooper argue that while numerous books for lawyers about AI exist, few focus on using the technology ethically. The authors also argue that while the legal profession has traditionally been slow to adopt new technologies, it can benefit from AI for several reasons. For example, AI technology can provide access to legal services for those in underserved areas like rural communities in the United States, Cooper said. "AI can be a game changer in terms of provision of legal services," he said. However, providing more education is the key to helping legal professionals understand AI technology. "The law school curriculum is not teaching AI or any technologies to the students, so there is a huge skill gap," Kompella said. Cooper added, "The skill sets of prompt engineering, of knowing how to use these AI tools and the dangers that come with them, should be rote in law schools now right from the first year. Those law schools around the world that embrace this idea are future-proofing their students. They're not going to have to play catch up." Esther Shittu is an Informa TechTarget news writer and podcast host covering artificial intelligence software and systems. Shaun Sutner is senior news director for Informa TechTarget's information management team, driving coverage of artificial intelligence, unified communications, analytics and data management technologies. Together, they host the Targeting AI podcast series