Alibaba.com B2B marketplace buys and sells with AI
In this episode of the Targeting AI podcast from AI Business, Esther Shittu and Shaun Sutner interview Justin Liu of B2B platform Alibaba.com.,
discussing his extensive experience in e-commerce and the evolution of B2B sourcing in the age of AI. Liu shares insights on the complexities of B2B transactions, the innovative AI tools being implemented to enhance buyer and seller experiences, and the rapid adoption of these technologies by small businesses. He also highlights the importance of supplier verification and security in B2B commerce, and how AI is transforming traditional roles in the industry. The conversation concludes with a look at Alibaba's global expansion efforts and the future of AI in the e-commerce sector.
Featuring: Just Liu, general manager, Alibaba.com U.S
In this episode, we cover how:
B2B sourcing is more complex than B2C transactions.
AI can simplify the tedious processes in B2B sourcing.
Alibaba.com focuses on helping buyers and sellers with AI.
AI adoption is growing rapidly among professional buyers.
AI enhances supplier verification and transaction security.
AI is transforming traditional sales roles in B2B.
AI helps lower the entry barrier for small businesses.
To learn more about generative AI and 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:
Alibaba, Nvidia Unite for AI Development and Cloud Growth
Alibaba Cloud targets full-stack AI dominance
Alibaba unveils Accio Agent for global trade
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Changing enterprises' misconceptions about AI
Some think AI is just a trend and that we are on the verge of a bubble. That is not the case for Arun Subramaniyan, of Articul8. This enterprise AI vendor offers customers a platform for developing and deploying customized generative AI applications. In this Targeting AI podcast, Subramaniyan discusses some of the misconceptions enterprises have about implementing AI technology and the significance of measuring ROI.
Featuring: Arun Subramaniyan, CEO and founder of Articul8
In this episode, we cover how:
AI is a necessity for solving complex problems, not just a trend.
Enterprises struggle with data synthesis and knowledge discovery.
Customer data remains secure within its environment.
Open source is crucial for the evolution of AI technology
Many enterprises misunderstand the complexities of AI implementation.
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:
How business leaders are measuring generative AI's ROI
AI regulation and the open source community
Intel-Backed Generative AI Company Launches Aerospace Platform at Paris Air Show
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Breaking news: What Nvidia's $5 trillion milestone means for AI
In this special news analysis edition of the Targeting AI podcast from AI Business, Esther Shittu and Shaun Sutner discuss Nvidia's historic achievement on Oct. 29 of becoming the first company to reach a $5 trillion market valuation with R "Ray" Wang of Constellation Research. The conversation explores the implications of this milestone for enterprise AI technology, the current AI boom, and the potential for a bubble in the market. They also touch on Nvidia's market position and the concerns surrounding monopoly in the context of the ongoing U.S.-China AI war.
Featuring R "Ray" Wang, founder and analyst at Constellation Research
In this episode, we cover how:
Nvidia's valuation reflects the growing importance of AI technology.
The AI market is expected to continue expanding significantly.
There is a potential for an AI bubble if job creation does not keep pace with AI advancements.
Entrepreneurship in AI is thriving, with small companies achieving significant revenue.
The emergence of AI exponentials is disrupting traditional business models.
Nvidia's dominance is partly due to geopolitical factors, particularly the U.S.-China AI war.
Concerns about monopolistic practices exist but are complicated by the competitive landscape.
The future of AI jobs remains uncertain as automation replaces traditional roles.
To learn more about Nvidia, generative AI and 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:
Nvidia unveils new AI hardware-software approach for industrial AI
Nvidia's deal with rival AI chipmaker Intel
The AI chip giant becomes first company to cross $5 trillion threshold
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Breaking News: Impact of the AWS Outage on AI Applications
In this breaking news analysis episode of the Targeting AI podcast from Informa TechTarget's AI Business, Esther Shittu and Shaun Sutner discuss the recent AWS outage that disrupted numerous websites and services, including AI applications such as widely used generative AI models from OpenAI and Anthropic. Tech analyst David Nicholson provides insights into the causes of the outage, emphasizing the importance of multi-site redundancy for enterprises relying on cloud services. The discussion also touches on the implications for AI applications and the need for businesses to consider redundancy options to prevent future disruptions.
Featuring: David Nicholson, analyst, The Futurum Group
In this episode, we cover how:
AWS experienced a major outage due to DNS problems.
The outage affected several large language models.
Multi-site redundancy is a way to prevent future disruptions.
Enterprises need to invest in redundancy for cloud services.
AI applications are not the cause of outages but are affected by them.
Cloud services have become more resilient over time.
Companies must be proactive in ensuring service continuity.
The cost of redundancy can be high, but it is necessary.
Smaller cloud providers may not offer the same level of resilience.
To learn more about generative AI, agentic AI and AI cloud services, check out AI Business from Informa TechTarget.
To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech.
References:
Prepare for a cloud outage with these preventive steps
Beware of over-reliance on U.S.-based cloud giants
Generative AI models from Anthropic and OpenAI
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Streaming data and generative AI: Confluent's approach
In this episode of the Targeting AI podcast from AI Business, Shaun Sutner and Esther Shittu interview Sean Falconer of streaming data platform vendor Confluent. They discuss Confluent's AI strategy, the importance of real-time data management, and the integration of generative AI and multi-agent systems into business processes. Falconer emphasizes the need for high-quality data and the advantages of open source technologies like Apache Kafka and Flink. The conversation also touches on the challenges of implementing AI systems and the future direction of AI technology at Confluent.
Featuring: Sean Falconer, senior director of AI Strategy at Confluent.
In today's episode, we cover how:
Confluent focuses on real-time data processing and management.
Generative AI requires fresh, relevant data to be effective.
Data quality should be enforced at the source, not downstream.
Multi-agent systems can operate continuously and autonomously.
Confluent partners with major AI model providers for integration.
Reliability and testing are critical challenges in AI development.
The future of AI at Confluent includes building support for ambient agent experiences.
To learn more about AI, open source and agentic systems AI, check out AI Business.
To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech.
References:
Confluent, streaming data and agentic AI
Confluent and Databricks work together to simplify AI development
What is data streaming?
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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