GenAI proponents exploring its use alongside infrastructure-as-code
(2023/09/11)
- Reference: 1694407572
- News link: https://www.theregister.co.uk/2023/09/11/gartner_gen_ai/
- Source link:
Generative AI boosters are beginning to explore how the technology could be used to augment infrastructure as code tools, according to Arun Chandrasekaran, a distinguished VP analyst at Gartner.
Speaking at the analyst firm's Symposium in Australia today, Chandrasekaran said he's aware of very early interest in the application of GenAI to IT infrastructure. He said we're nowhere near developers being able to use AI to order infrastructure – "Alexa: build me a K8s cluster" – but developers are already pondering how models could use logfiles to analyze an org's IT. As suggesting code is already one of the most prominent applications of generative AI, the potential for binary brainboxes to recommend infrastructure recipes needed to execute code is tantalizing.
AI was, unsurprisingly, the topic of the Symposium keynote – the first time Gartner has dedicated the opener at its flagship conference to a single topic. The session saw distinguished VP analyst Don Scheibenreif and senior director of research and advisory Neha Kumar articulate Gartner's belief that generative AI will quickly make an impact on back office tasks such as assisting developers to write code, or helping users of personal productivity tools to work faster and more efficiently.
[1]
But the two analysts said back office tools like GitHub Copilot or the generative AI augmentations for Google Workspaces will not deliver competitive advantage. Nor do text-to-text tools like ChatGPT. Everyone can access them and learn how to use them, so they represent "table stakes."
[2]
[3]
More complex AI can have greater impact.
[4]Gartner says hold onto your wallets as SAP's cloud pitch trades control for convenience
[5]AI to replace 2.4 million jobs in the US by 2030, many fewer than other forms of automation
[6]Reports of the PC's death are greatly exaggerated, says IDC
[7]Intel's Tower bid has shuffled off this mortal coil – so what about foundry plans?
Scheibenreif used the example of Khan Academy's "Khanmingo" chatbot – which offers students an interactive tutor – as an example of what Gartner considers "game-changing AI." But he and Kumar warned that building that sort of tool is harder, more expensive, and riskier than using back office AI.
Securing funding for such efforts, the pair warned, is hard. Many chief financial officers are underwhelmed by digital transformation, so building a case for big AI investments will be hard.
Chandrasekaran, in a session titled "Beyond the ChatGPT Hype: Deploying Generative AI in the Enterprise," rated developing complex AI in-house as the most complex and expensive way to adopt the tech. He suggested that years of work is necessary to blend public and private models, not to mention adding an org's own data.
[8]
But that doesn't mean it isn't going to happen. He's aware of upstart vendors trying to commoditize the tools required to develop and deploy AI in myriad ways – and said venture capitalists are very interested in funding such organizations. ®
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[4] https://www.theregister.com/2023/09/01/gartner_rise_with_sap/
[5] https://www.theregister.com/2023/09/06/generative_ai_jobs_forrester_report/
[6] https://www.theregister.com/2023/08/29/pc_bounceback_idc/
[7] https://www.theregister.com/2023/08/18/intel_tower_acquisition/
[8] https://pubads.g.doubleclick.net/gampad/jump?co=1&iu=/6978/reg_software/aiml&sz=300x50%7C300x100%7C300x250%7C300x251%7C300x252%7C300x600%7C300x601&tile=4&c=44ZP7lQtjLf8oFKjHHFkJETQAAAUw&t=ct%3Dns%26unitnum%3D4%26raptor%3Dfalcon%26pos%3Dmid%26test%3D0
[9] https://whitepapers.theregister.com/
Speaking at the analyst firm's Symposium in Australia today, Chandrasekaran said he's aware of very early interest in the application of GenAI to IT infrastructure. He said we're nowhere near developers being able to use AI to order infrastructure – "Alexa: build me a K8s cluster" – but developers are already pondering how models could use logfiles to analyze an org's IT. As suggesting code is already one of the most prominent applications of generative AI, the potential for binary brainboxes to recommend infrastructure recipes needed to execute code is tantalizing.
AI was, unsurprisingly, the topic of the Symposium keynote – the first time Gartner has dedicated the opener at its flagship conference to a single topic. The session saw distinguished VP analyst Don Scheibenreif and senior director of research and advisory Neha Kumar articulate Gartner's belief that generative AI will quickly make an impact on back office tasks such as assisting developers to write code, or helping users of personal productivity tools to work faster and more efficiently.
[1]
But the two analysts said back office tools like GitHub Copilot or the generative AI augmentations for Google Workspaces will not deliver competitive advantage. Nor do text-to-text tools like ChatGPT. Everyone can access them and learn how to use them, so they represent "table stakes."
[2]
[3]
More complex AI can have greater impact.
[4]Gartner says hold onto your wallets as SAP's cloud pitch trades control for convenience
[5]AI to replace 2.4 million jobs in the US by 2030, many fewer than other forms of automation
[6]Reports of the PC's death are greatly exaggerated, says IDC
[7]Intel's Tower bid has shuffled off this mortal coil – so what about foundry plans?
Scheibenreif used the example of Khan Academy's "Khanmingo" chatbot – which offers students an interactive tutor – as an example of what Gartner considers "game-changing AI." But he and Kumar warned that building that sort of tool is harder, more expensive, and riskier than using back office AI.
Securing funding for such efforts, the pair warned, is hard. Many chief financial officers are underwhelmed by digital transformation, so building a case for big AI investments will be hard.
Chandrasekaran, in a session titled "Beyond the ChatGPT Hype: Deploying Generative AI in the Enterprise," rated developing complex AI in-house as the most complex and expensive way to adopt the tech. He suggested that years of work is necessary to blend public and private models, not to mention adding an org's own data.
[8]
But that doesn't mean it isn't going to happen. He's aware of upstart vendors trying to commoditize the tools required to develop and deploy AI in myriad ways – and said venture capitalists are very interested in funding such organizations. ®
Get our [9]Tech Resources
[1] https://pubads.g.doubleclick.net/gampad/jump?co=1&iu=/6978/reg_software/aiml&sz=300x50%7C300x100%7C300x250%7C300x251%7C300x252%7C300x600%7C300x601&tile=2&c=2ZP7lQtjLf8oFKjHHFkJETQAAAUw&t=ct%3Dns%26unitnum%3D2%26raptor%3Dcondor%26pos%3Dtop%26test%3D0
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[4] https://www.theregister.com/2023/09/01/gartner_rise_with_sap/
[5] https://www.theregister.com/2023/09/06/generative_ai_jobs_forrester_report/
[6] https://www.theregister.com/2023/08/29/pc_bounceback_idc/
[7] https://www.theregister.com/2023/08/18/intel_tower_acquisition/
[8] https://pubads.g.doubleclick.net/gampad/jump?co=1&iu=/6978/reg_software/aiml&sz=300x50%7C300x100%7C300x250%7C300x251%7C300x252%7C300x600%7C300x601&tile=4&c=44ZP7lQtjLf8oFKjHHFkJETQAAAUw&t=ct%3Dns%26unitnum%3D4%26raptor%3Dfalcon%26pos%3Dmid%26test%3D0
[9] https://whitepapers.theregister.com/
Beware smarting SMARTR startup vendors with upstart monikers. They might take offence ....
...... and demand satisfaction
More complex AI can have greater impact.
More complex AI will undoubtedly deliver greater impact and overwhelming competitive and oppositional advantage and will certainly be quite naturally expensive for all those who would not themselves possess, but would desire and be required to both lease purchase and need to have wielded for them, by those and/or that which are so blessed with such assisted information deploying revolutionary knowledge and valuable novel hindsight rich foresight supplied by what is best easily and accurately described and labelled, for simple widespread understanding of workings in a vast array of undeniably complex related fields, as SMARTR .... SMARTR Mentoring Analysis Reporting Titanic Research.
And whenever both a Greater IntelAIgent Game Changer and Great Game-changing are all risks and substantial crippling losses catastrophically suffered by wanton and wilfully negligent non adopters and shady shadowy players expecting past successful defensive systemic strategies of a previous analogue age to once again prevail and prevent a leading change of outright command and control into alien hands, hearts and minds in a now fully remotely virtualised universal environment.
And such is the current here and now situation so to suggest that years of hard work to blend public and private models, not to mention adding an org's own data, are necessary to employ and enjoy the resultant SMARTR rewards and advantages, are misleading whenever such works be already undertaken and taken care of by SMARTR AIgents.