Google Cloud Next 2024: Building an AI advantage
Google's data heritage could be just the right ingredient as it takes on the AI market at scale
This week has seen Google Cloud’s annual Next conference in full swing, with the hyperscaler having made major announcements on generative AI and the infrastructure necessary to support it.
Having spent the past year playing catch-up with Microsoft and OpenAI, Google Cloud is now in a place where it’s ready to press its advantage in AI, years after the company first declared itself “AI first”. But has it succeeded in this mission, and if so – what are the tangible benefits for Google Cloud customers?
In this episode, recorded live at Google Cloud Next 2024 Rory speaks to Bola Rotibi, Chief of Enterprise Research, CCS Insight, to explore some of the most notable trends at the event and unpack why Google has a strong advantage in the AI space.
Highlights
“What's been actually really kind of interesting, from my perspective, is actually seeing a lot of the terms that Google's pushed out, like ‘grounded in search’, ‘grounded in your data’, which I thought was quite interesting because it's really trying to reinforce their heritage and they really leaned into their data heritage, the supporting infrastructure, the platform.”
RELATED WHITEPAPER
“The IT world, or just the world in general has always got lots and lots of different players. The fact is that they've done a lot of work, a lot of optimization, they've got their own models but they absolutely recognize that other people will want different models. So they want third-party models and they want open source models, they want their own models. So [Google Cloud has] relationships with Anthropic, Hugging Face, all of these kinds of things and they want to give all of those opportunities and flexibility of choice.”
“What they've really pushed also is the story of a lot of clients that were initially on other cloud platforms. So they've come through and they've come through via the data analytics, the strength of Google's data infrastructure and the amount of work that they've done over the decades.”
Footnotes
- Google Cloud Next 2024: All the news and announcements live
- Gemini Code Assist could be Google's secret weapon to challenge GitHub Copilot
- Google Cloud doubles down on AI Hypercomputer amid sweeping compute upgrades
- Google Cloud targets ‘AI anywhere’ with Vertex AI Agents
- Anthropic could be the champion AWS and Google need
- Google’s Hugging Face partnership shows the future of generative AI rests on open source collaboration
- Microsoft Copilot review: AI baked into your apps
- You’re going to have an AI copilot for everything you do – and you’ll probably hate it
Subscribe
- Subscribe to The IT Pro Podcast on Apple Podcasts
- Subscribe to The IT Pro Podcast on Spotify
- Subscribe to the IT Pro newsletter
- Join us on LinkedIn
-
Slicing through the static: why data quality is the channel’s ultimate competitive advantageIndustry Insights There's real risk from fragmented telemetry for channel partners...
-
Why IT leaders need to be involved in layoff decision-making to avoid AI washingIn-depth Those who sit closest to where AI is deployed are often overlooked, despite being better placed to determine what AI can automate and where human expertise remains critical
-
AI's operational blind spotsPodcast We talk to Tim Pfaelzer, SVP and GM EMEA at Veeam, about operational blind spots, what they mean for businesses, and how they can balance their desire for a technical edge
-
Agents on the frontline: How Box is using AI to supercharge cybersecurityPodcast How can enterprises adopt AI agents in a safe and secure manner?
-
Google's Spirit Airlines auction & TrendAI insider threat reportPodcast Google's Spirit Airlines auction & TrendAI insider threat report
-
Google targets AI cost efficiency with new FinOps features for Gemini EnterpriseNews New cost control features and subscription options for Gemini Enterprise look to bring down spiralling AI costs
-
Google just spent $10 million in an auction for Spirit Airlines data – 100 million emails, 500 million Microsoft Teams chats, and 30 million lines of code will be used to improve AI models and productsNews AI developers are struggling to find enough data to train their models, sparking a bidding war for failed Spirit Airlines deidentified data
-
Can responsible AI beat hallucinations?Businesses are more eager than ever to implement AI in their workflows, but ambition doesn’t always translate into success
-
What the OpenAI rogue bot story really says about the state of AI securityPodcast
-
Oracle integrates Google's Gemini AI models into enterprise appsThe deal aims to give broader access to Gemini models that can support AI agents and accelerate development
