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IBM’s leadership in genAI: Insights from Manav, CTO of IBM Canada

New Post has been published on https://thedigitalinsider.com/ibms-leadership-in-genai-insights-from-manav-cto-of-ibm-canada/

IBM’s leadership in genAI: Insights from Manav, CTO of IBM Canada

At the recent Generative AI Summit in Toronto, I had the opportunity to sit down with Manav Gupta, the CTO from IBM Canada to explore the company’s current work in generative AI and explore their vision for the future. Here are the key insights from our conversation, highlighting IBM’s ecosystem leadership, industry impact, and strategies to navigate challenges in the generative AI landscape.

IBM’s position in the generative AI landscape

Manav began by emphasizing IBM’s commitment to ensuring that enterprises own their AI agenda. He stressed the importance of AI being open and accessible to organizations, individuals, and societies to foster growth. To this end, IBM leads with Watson X, a comprehensive platform that serves as both a model garden and a prompt lab. Watson X allows users to leverage IBM-supplied models, third-party models, or even fine-tune their own models for deployment on their preferred cloud or on-premises infrastructure.

One of the standout features of IBM’s approach is its focus on AI governance. Manav highlighted the critical need for enterprises to ensure that the AI they deploy is free from biases, hate speech, and other ethical concerns. IBM’s governance platform is designed to address these issues, ensuring that generative AI outputs are safe and unbiased.

The transformative impact of generative AI

When asked about the impact of generative AI across industries, Manav was unequivocal in his belief that this technology will touch every sector. He cited estimates that generative AI could add up to 3.5 basis points to global GDP, a staggering figure that underscores its potential. Industries such as banking, healthcare, telecommunications, and the public sector are poised to benefit significantly. 

Banking and Financial Services: Streamlining workflows and enhancing decision-making.

Public Sector and Healthcare: Unlocking data-driven efficiencies and improving service delivery.

Telecommunications: Transforming customer interactions and operational processes.

Manav explained that wherever there is a large corpus of data and existing workflows, generative AI can unlock human potential by automating mundane tasks and allowing employees to focus on higher-value activities.

Challenges in deploying generative AI

Despite the immense potential, Manav acknowledged that deploying generative AI solutions is not without its challenges. One of the primary hurdles is client maturity. Many organizations are still in the experimental phase, trying to understand both the opportunities and the risks associated with this technology. Additionally, integrating generative AI with existing data systems is a significant challenge. Enterprises often have high-quality data, but it is locked in silos across departments such as finance, HR, and procurement. Accessing and unifying this data in a timely manner is a complex task.

Another major challenge is the resource intensity of generative AI. The specialized hardware required to run these models is expensive and often in short supply, leading to long lead times for deployment.

Future trends in generative AI

Looking ahead, Manav foresees several key trends in the generative AI market. He predicts that models will continue to improve, with a shift from large language models (LLMs) to more fit-for-purpose smaller models. These smaller models, often referred to as small language models (SLMs), are more efficient and tailored to specific use cases. Manav also highlighted the rise of agentic AI, where AI systems will have greater autonomy to execute tasks on behalf of humans, particularly in high-value areas like software engineering and testing.

Another trend is the increasing importance of multi-modal models, which can process and generate different types of data, such as images and text. Manav gave an example of how enterprises could use multi-modal models to analyze images and make decisions based on that analysis, opening up new possibilities for automation and efficiency.

Key takeaways from Manav’s presentation

Manav concluded our interview by summarizing the key takeaways from his summit presentation.

Be an AI value creator, not just a consumer. Don’t just use AI—figure out how to make it work for you.

Start with models you can trust. Whether it’s IBM’s Granite models or open-source alternatives, experiment with reliable AI solutions.

Don’t treat AI governance as an afterthought. Privacy, security, and responsible AI should be built into the foundation of your AI strategy.

Watch Manav’s presentation at the Generative AI Summit in Toronto.

IBM’s Granite models and InstructLab

During his presentation, Manav also delved into IBM’s Granite models, a series of open-source foundation models designed for enterprise use. These models, which include specialized versions for time series and geospatial data, are trained on vast amounts of data and are optimized for performance and cost-efficiency.

IBM has also developed InstructLab, a novel methodology for adding enterprise data to LLMs without the need for extensive fine-tuning. This approach allows organizations to iteratively train models on their specific data, ensuring that the AI remains relevant and accurate for their unique use cases.

Conclusion

Manav’s insights underscore IBM’s leadership in the generative AI space, particularly in addressing the challenges of scalability, integration, and governance. As enterprises continue to explore the potential of generative AI, IBM’s Watson X platform and Granite models offer a robust foundation for innovation. With a focus on trust, transparency, and ethical AI, IBM is well-positioned to help organizations navigate the complexities of this transformative technology.

The Generative AI Summit series from the AI Accelerator Institute provides a platform for thought leaders like Manav to share their vision for the future of AI.

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The Secret to Winning UX in 2025: A Checklist You Can’t Ignore! #uxchecklist #uxdesign #uiux #uxtips #startup #saas #digitalproducts

60% of digital products fail to engage users effectively! The solution isn’t just about: - Adding flashy features - Following every design trend - Focusing solely on tech The real problem? Ignoring user-friendly design and usability. Here’s what happens when design is overlooked: - Users get frustrated and leave. - Engagement plummets. - Brand loyalty fades away. The solution? Blend user experience with simplicity and functionality. Here’s a 2025 UX checklist to get it right: ✔️ Design with real people in mind. ✔️ Ensure your product is seamless across all devices. ✔️ Make your product usable for everyone. ✔️ Don’t let slow loading times drive users away. ✔️ Gather feedback to improve the experience continuously. ✔️ Keep the design simple and easy to navigate. ✔️ Make sure users always know what to do next. This is how design and usability come together ↳ to create an unforgettable user experience. P.S. Want to create a product that’s both functional and beautiful? Drop me a DM today!

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From vision to practice for a just transition for all - Part 1.

A cross-regional South-South Policy Dialogue on energy, sustainable finance, and enterprises for and enhancing NDC ambition. The policy dialogue will be held between 20-21 November 2024 at the Just Transition Pavilion during the COP29. It is an ILO led event in joint collaboration and support from the UN-PAGE programme (that bring five agencies: ILO, UNEP, UNDP, UNIDO and UNITAR).

Watch From vision to practice for a just transition for all - Part 1!

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DevAI Raises $6M to Revolutionize Enterprise IT with Network Intelligence Agents

New Post has been published on https://thedigitalinsider.com/devai-raises-6m-to-revolutionize-enterprise-it-with-network-intelligence-agents/

DevAI Raises $6M to Revolutionize Enterprise IT with Network Intelligence Agents

In a major boost to enterprise IT, DevAI, a rising force in AI-powered IT solutions, has secured $6 million in an oversubscribed seed round led by Emergence Capital. The round also saw participation from Pear VC, Base10, and Benchstrength, following an earlier $1 million pre-seed investment from Pear VC.

DevAI is tackling a critical challenge in the $2.5 trillion IT software and services market: IT teams are bogged down by fragmented tools, unreliable system data, and an over-reliance on institutional knowledge. With enterprise IT professionals spending up to 80% of their time on KTLO (Keep the Lights On) activities—tasks essential to maintaining IT infrastructure but with minimal direct business impact—DevAI is stepping in with AI-driven solutions to optimize workflows and reduce downtime.

At the heart of DevAI’s offering is the DevAI Network Intelligence Engine, a system that aggregates insights from IT tools, industry best practices, and institutional expertise. The company’s first AI agent, Neo, is designed to streamline IT workflows, enhance security and compliance, and minimize time spent troubleshooting.

“IT professionals are the unsung heroes of modern enterprises, working around the clock to ensure IT systems stay online and networks are secure and performing their best,” says Susie Wee, cofounder and CEO of DevAI. “Our network AI agents give them the insights they need to proactively address issues and eliminate inefficiencies so they can focus on business priorities and innovation instead of constant firefighting.”

Wee, a former Cisco executive, is no stranger to transforming enterprise IT. She earned her Ph.D. from MIT and previously founded DevNet, Cisco’s developer program, which grew to over half a million members. She now brings that experience to DevAI, aiming to arm IT professionals with AI tools that capture institutional knowledge, enrich IT infrastructure data, and accelerate productivity.

Wee’s cofounder, Edwin Zhang, brings deep expertise in enterprise technology, cloud, and software platforms. He and Wee have collaborated for over a decade on award-winning enterprise solutions.

“Neo isn’t just another AI tool—it’s a tech buddy for IT professionals,” says Zhang. “Neo works alongside them, gathering information from across their systems, reducing the time they spend troubleshooting, and empowering them to solve complex problems faster.”

Addressing the Enterprise IT Knowledge Gap

Enterprise IT teams struggle with inconsistent “source of truth” systems, where different IT tools provide conflicting information on configurations, assets, and infrastructure. DevAI’s technology gathers and enriches data from multiple sources, creating an accurate and centralized repository of institutional knowledge. The solution enables IT teams to:

Reduce MTTI (Mean Time to Identify) and MTTR (Mean Time to Resolve) incidents, minimizing costly downtime.

Improve source of truth accuracy by consolidating and validating data from different IT tools.

Capture and retain institutional knowledge, preventing information loss when tenured IT professionals leave an organization.

Free up domain experts from repetitive tasks, allowing them to focus on strategic initiatives.

Investor Confidence in DevAI’s Market Potential

Emergence Capital’s backing signals confidence in DevAI’s ability to transform enterprise IT operations.

“We couldn’t be more excited to partner with Susie and the DevAI team to transform enterprise IT management, bringing much-needed automation and intelligence to an area ripe for innovation,” says Santi Subotovsky, General Partner at Emergence Capital. “When we talked to DevAI’s sophisticated enterprise customers and heard how DevAI aligns with their growing demand for smarter, AI-powered tools to reduce costs and enhance productivity, we were convinced DevAI was creating real value for enterprises.”

Mar Hershenson, founding managing partner at Pear VC, echoes this sentiment: “Susie founded DevNet and learned firsthand from the community the problem of managing complex enterprise networks. Using an agentic framework to optimize implementations and maintenance will allow these experts not only to spend time on more strategic matters but also increase network reliability.”

Real-World Impact: Partnering with Industry Leaders

Beyond investor support, DevAI is already working with major enterprises, including FedEx and Cigna, to refine its AI-driven solutions through real-world deployment.

Aryo Kresnadi, Technical Director at FedEx, emphasizes the importance of DevAI’s collaboration: “We need to architect our network to support our business today and for the next 5, 10, and 20 years. Working closely with DevAI has allowed us to design solutions for critical areas we have not been able to address to date.”

The Road Ahead: Scaling AI for Enterprise IT

With its fresh injection of capital, DevAI plans to expand its AI-powered agent solutions, onboard more enterprise partners, and enhance its platform’s capabilities. The company is building a thriving IT community, inviting enterprises to join as design partners to shape the next generation of AI-driven IT management.

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