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What’s Next for Personalization on Google Cloud
Customer shopping behavior has changed for good. With fewer in-store shopping visits retailers have had to shore up their digital storefronts and explore new ways to meaningfully engage with their customers.
Delivering a superior customer experience has become even more of a differentiator for the early movers and personalized recommendations have emerged as one of the strongest potential drivers of revenue lift.
But as many retailers have discovered delivering recommendations at scale can actually be quite complex and time consuming.
Learn how to deliver highly-personalized product recommendations with Google Cloud Recommendations AI.
Recommendations AI is now fully open access and self-serve, with more built-in integrations with Google Shopping Merchant Center and Google Analytics, as well as more controls over how you create recommendation pipelines and manage your costs.
You will also hear how Google Cloud partners like Qubit and BigCommerce have successfully deployed Recommendations AI for their customers and made us an integral part of their solution offerings.
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Becoming Future-Proof: AI-Powered Integrated Business Planning on Google Cloud
If there’s one thing that the pandemic will leave us with it’s this: A deep desire to be better prepared. Not prepared for the next possible catastrophe because that’s hard to do, but better prepared for the repercussions of such disaster.
In this video, Stephan de Barse, Executive Vice President, o9 Solutions, talks about some of the ripple effects of large-scale disruption including demand variability and supply variability.
He shares practical insights on how large retailers and manufacturers can leverage next-generation technology to improve demand forecasting, visibility, and drive a faster response while optimizing their decision-making processes.
He also shares learnings from COVID-19 as well as the critical capabilities needed by industry leaders to become more agile and resilient in the post-pandemic world.
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How Anthos Helps Organizations Implement Multi and Hybrid Cloud Strategy
Organizations have become increasingly focused on using modernization solutions to build competitive advantage, for faster time to market, serve customers better and seamlessly operate in hybrid and multi-cloud environments. Anthos by Google Cloud, a managed application platform plays an important role in application modernization and also in empowering customers to deploy a hybrid or multi-cloud strategy with opensource technologies and platforms like Kubernetes.
Watch the video to refer to the real use-cases of Anthos for application modernization and hybrid/multi cloud deployment across retail, digital natives, banking and manufacturing space.
Also, explore the latest tool, Migrate for Anthos if you are a traditional enterprise looking to skip rewriting of applications and lift-and-shift process!
IBL Education’s GenAI-based chat mentor with Google
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With more than 6 years of experience in building open source and Generative AI in education at scale, ibleducation.com continues to evolve its approach and services. More recently, the company became an education-focused Vertex AI integrator. They provide enterprises and academic institutions with a platform to build, train and securely customize large language models (LLMs) for interactive mentors using Google’s Vertex AI.
“The education industry only recently began understanding the value of Generative AI with open source and the opportunities it presents,” says Miguel Amigot II, Chief Technology Officer at ibleducation.com. “We’re providing the chance to build a new type of learning, mentoring, and analytics platform that gives organizations total control over their training methods, data, and more, without locking into one vendor.”
Organizations large and small, including Fortune 500 companies and leading universities institutions, use ibleducation.com to support their learners, allow educators to develop coursework, and provide engineers with a solid platform to build on.rely on it to power their learning strategies.
Recently, ibleducation.com chose to partner with Google Cloud to improve its platform and scale beyond its base of millions of users.
Harnessing the power of GenAI in education and training
ibleducation.com initially began working with Google Cloud to unify its education data strategy to drive real-time and predictive analytics.
“Google Cloud outperforms others when it comes to maintaining control over algorithms and general data governance,” says Amigot. “We’re fortunate to be able to maintain ownership of our models while maintaining a pay-per-use pricing model. This is critical for our business. It allows our clients to avoid lower-value maintenance tasks, focus on innovation and user experience, and not worry about excessive costs.”
In the past, because of the high costs and need for AI and engineering talent to produce large language models, schools have been unable to take full advantage of open-source education technologies. Together, ibleducation.com and Google Cloud democratize access to AI-enabled tools for educators worldwide.
With a strong analytics and AI foundation, ibleducation.com has been able to personalize, translate, and create education content faster than before. This has been especially effective in improving accessibility, as automated translation and repurposing ensures those with visual and hearing impairments can interact with the content.
“Google Cloud enables us to reduce the total cost of building, running, and maintaining large language models by more than 70%,” says Amigot. “We’ve seen language model hosting costs decrease before, but nothing like this.”
Bringing AI-powered content creation to educators
Vertex AI has been especially useful in creating content, helping ibleducation.com to dramatically scale out its learning materials. Usage-based pricing mixed with an open-source model gives ibleducation.com the resources to support its users in developing evolving, valuable learning experiences to serve people worldwide.
Additionally, Google Cloud powers ibleducation.com’s Generative AI-based mentors, which provides a one-to-one learning experience to students and professionals looking for tailored skills development.
“The mission is to provide educators with a centralized system wherein they can manage everything from indexing data about customer courses to designing and facilitating UI/UX for users’ digital mentors,” says Amigot. “Google Cloud has helped us cover all of these bases.”
ibleducation.com allows users to create virtual mentors that provide personalized teaching, assess student knowledge, guide students through skills and learning paths, and offer robust learning analytics. Text-to-text and speech-to-speech interfaces can be offered over Slack, Discord, text message-based bots, web scripts, and LTI integrations.
“AI Mentor has been a very effective tool for our users because it adapts to the needs of educators and organizations very quickly,” says Amigot. “We’re seeing people use it for teaching assistance, marketing and administration, and a lot more. Vertex AI allows us to have many models for any variety of purposes.”
Looking forward, ibleducation.com is looking to continue taking personalized learning to new heights.
“From a mission standpoint, we want to expand to reach all the organizations not currently served by online education through our platform, analytics, and other AI-powered services,” says Amigot. “Our relationship with Google Cloud is instrumental in achieving our goal to democratize access to next-generation educational capabilities to more communities and organizations around the globe.”
Ready to take the next step? Join our upcoming GenAI workshop for higher education to learn how Google’s AI tools can help education institutions or explore our EdTech solutions to see how you can make education more personal, safe, and accessible with 100+ cutting-edge products.
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Breakthroughs in artificial intelligence (AI) have captured the imaginations of business and technical leaders alike. The AI techniques underlying these breakthroughs are finding diverse application across every industry. Early adopters are seeing results, particularly encouraging is that AI is starting to transform processes in established industries, from retail to financial services to manufacturing.
However, an organization’s effectiveness in applying these breakthroughs is anchored in the basics: A disciplined foundation in capturing, preparing and analyzing data.
Data scientists spend up to 80% of their time on the “data wrangling,” “data munging” and “data janitor” work required well before the predictive capabilities promised by AI can be realized.
Capturing, preparing and analyzing data creates the foundation for successful AI initiatives. To help business and IT leaders create this virtuous cycle, Google Cloud has prepared a CIO’s guide to data analytics and machine learning that outlines key enabling technologies at each step. Crucially, the guide illustrates how managed cloud services greatly simplify the journey—regardless of an organization’s maturity in handling big data.
This is important because, for many companies, the more fundamental levels of data management present a larger challenge than new capabilities like AI. “Management teams often assume they can leapfrog best practices for basic data analytics by going directly to adopting artificial intelligence and other advanced technologies,” noted Oliver Wyman consultants Nick Harrison and Deborah O’Neill in a recent Harvard Business Review article (aptly titled If Your Company Isn’t Good at Analytics, It’s Not Ready for AI). “Like it or not, you can’t afford to skip the basics.
Building on new research and Google Cloud’s own contributions to big data since the beginning, this guide walks readers through each step in the data management cycle, illustrating what’s possible alongside examples.
Specifically, the CIO’s guide to data analytics and machine learning is designed to help business and IT leaders address some of the essential questions companies face in modernizing data strategy:
- For my most important business processes, how can I capture raw data to ensure a proper foundation for future business questions? How can I do this cost-effectively?
- What about unstructured data outside of my operational/transactional databases: raw files, documents, images, system logs, chat and support transcripts, social media?
- How can I tap the same base of raw data I’ve collected to quickly get answers as new business questions arise?
- Rather than processing historical data in batch, what about processes where I need a real-time view of the business? How can I easily handle data streaming in real time?
- How can I unify the scattered silos of data across my organization to provide a current, end-to-end view? What about data stored off-premises in the multiple cloud and SaaS providers I work with?
- How can I disseminate this capability across my organization—especially to business users, not just developers and data scientists?
Because managed cloud services deal with an organization’s sensitive data, security is a top consideration at each step of the data management cycle. From data ingestion into the cloud, followed by storage, preparation and ongoing analysis as additional data flows in, techniques like data encryption and the ability to connect your network directly to the Google Cloud must reflect data security best practices that keep data assets safe as they yield insights.
Wherever your company is on its path to data maturity, Google Cloud is here to help. We welcome the opportunity to learn more about your challenges and how we can help you unlock the transformational potential of data.
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