Enterprise hits and misses - generative AI surges past robotics, but why? Deutsche Bank tests financial markets - will they hold?

Lead story - AI gut check - why is generative AI surging ahead of robotics?

Say what you like about generative AI - I've said plenty (I also believe Microsoft is way off base asserting ChatGPT4 is the "sparks" of AGI, but that's another story).

Still, generative AI is surging, compared to the difficulties that physical robots have encountered. Chris explores this topic in Why it’s simpler for AIs to write about art than for robots to do your laundry:

Teaching a robot that a cup is a cup, let alone training the machine to put it on a shelf, is an incredibly complex engineering and programming task. And that’s in spite of all those videos of Boston Dynamics robots running, jumping, and doing somersaults.

ChatGPT can train on the open Internet, and produce content from that ingested data in controlled settings. But moving about, amidst other humans, is not a controlled setting. Still, as the CEO of Sanctuary AI tells Chris, there are robotics use cases that work:

The automation of all the things that people can do without thinking is not within sight of modern technology. Not now, nor in the near- or medium-term future. But, for example, the movement of goods from place to place is more like low-hanging fruit. Those are the kinds of tasks that you can automate with technologies that are within sight.

At diginomica, we've forayed into the generative AI hype festival in search of relevant enterprise use cases. We've found a number of them, though I characterize these as "evolutionary," not the "revolutionary" some are implying. Phil picks up this topic in Generative AI 'knows nothing' says Software AG's CPO. So what are the enterprise use cases?. Coding is an example of an evolutionary use case. As per Phil:

For example, in the realm of integration, ChatGPT could be helpful when developers are creating mappings between APIs, when the fields in one dataset need to be matched to fields with different names in another dataset.

Phil quotes Software AG's CPO, Dr. Stefan Sigg:

That's typically something which can be tedious and error-prone. Even in the past, there has been some promises that AI would be helping that a lot. But that wasn't really the case, because there was a lack of data behind the model.

My intention is not to throw cold water but to push for precision. When you need humans-in-loop, you aren't in revolutionary mode (alas, that's why Internet-based disinformation-at-scale is the most revolutionary generative AI use case to date, along with commodity publishing, as per black hat SEO-rigging web sites).

And yet, as I wrote in my Workday AI/ML Innovation Summit review, I can see the enterprise taking the lead in making generative AI truly useful. Finally, the enterprise tech spank tunnel - with its comparatively high guardrails on data quality in mission critical systems - just might come in handy.

Diginomica picks - my top stories on diginomica this week

• Can analytics make a company better? The answer isn't as easy as you think - Neil issued a scorcher on our analytics infatuation: "I wonder if the focus on technology, data modernization, and the "democratization of analytics" overlooks a more fundamental problem: it's still too difficult to apply."
• Elsevier sees promise in small language models and graph data - Large Language Models grab the headlines, but George finds progress in other areas: "Academic researchers are less forgiving of issues like hallucinations and misinformation creeping into their narratives than consumers."
• How McDonald's took complaint resolution from 10 days to 10 seconds with digital vouchers - 10 days to 10 seconds? Okay, Stuart has my attention.
• ​​One of the biggest banks in the Philippines accelerates digital inclusion via low-code and open banking - Gary filed a nifty use case of a bank that chose to build a homegrown solution, but in line with industry norms: "In the end, the decision was taken to embrace the standards being driven by BIAN - the Banking Industry Architecture Network."

Vendor analysis, diginomica style. Here's my three top choices from our vendor coverage:

• Accenture to shed 19,000 jobs, but CEO Julie Sweet says the big transformational deals are still happening -  Stuart makes sense of Accenture's yin/yang: "A solid enough quarter and the message from Sweet is inevitably upbeat. But the note of caution running through the forward guidance and, of course, the job cuts, are a reminder of the current volatility in the wider economy."
• Workday AI/ML Innovation Summit - how Accenture shifted to a skills-based organization with Skills Cloud - I picked my underrated story from Workday's annual analyst event: customer impact, adoption and scale are the three factors that get my attention.
• NVIDIA paves more roads to USD - George files his first missive from NVIDIA's GTC Conference: "The native cloud support later this year might bring a little momentum to USD as the universal glue for the Industrial Metaverse. It could also plant the seeds for new tools to generate digital twins. However, more work will be required to standardize ways of describing how things function rather than just how they look."

Adobe Summit - diginomica team coverage. As expected, Adobe had plenty to say about generative AI, and, understandably, not much to say about the Figma acquisition status, but there was more:

• Adobe Summit - generative AI takes a front-row seat - Barb hits in the major themes of the show. There is CDP news to consider, along with a notable update Adobe calls the "content supply chain."
• Adobe Summit - with Firefly, Adobe adds accountability to generative AI -  If you're like me, you're already getting weary of 'we-have-it-too' generative AI announcements. But with Adobe's heavy investments in Creative Cloud, they had to stake their claim here. And, as Phil reports from Las Vegas, they are setting a higher bar than their peers when it comes to the ethics of sourcing training data. Referring to the "Wild West" of generative AI, Phil concludes: "Adobe is definitely the good guy in this analogy, affirming that it wants to bring 'accountability, responsibility and transparency' to bear in its use of generative AI."
• Adobe Summit - General Motors drives personalization up a gear with Experience Cloud - Mark filed a couple of Summit uses cases, including GM and this one: EY uses Adobe technology to create marketing campaigns with a competitive edge.

A couple more vendor picks, without the quotables:

• Celonis targets “government mavericks” to improve public sector processes - Derek
• Nationwide moves beyond customer experience surveys to conversational analytics with Qualtrics XM Discover - Derek

Best of the enterprise web

My top seven

• Meltdown in Deutsche Bank Shares Shows Banking Crisis Is Not Yet Over - Though Deutsche Bank will surely be saved/bailed out one way or the other, the cascading financial market stress is clearly an impediment to better economic times. I believe much of this is a banking market correction based on the global rise in interest rates, but an irrational human factor can come into play. How much faith we put in the banking system may dictate how grim this gets. Pulling money en masse out of relatively stable banks has a way of making them unstable pretty quickly.
• AWS takes a hit in latest round of Amazon layoffs - Ron Miller puts the AWS job hit into context: "Against that backdrop, the layoffs shouldn’t come as a surprise. In fact, the cloud infrastructure market overall has been experiencing slowing growth. After years of runaway numbers, cloud spending is being curtailed, and it’s starting to have an impact on the market."
• More skills are needed to help AI plug skills gaps - Joe McKendrick bears down on the AI skills paradox, something the AI handwavers seem to lose track of: "'AI and machine learning is smart -- but it isn't ready to implement itself,' the survey report's authors point out. 'It's difficult to find skilled people who can work with the technology and the data to optimize outcomes.'"  
• ChatGPT in the emergency room? The AI software doesn't stack up - High risk doesn't always mean high rewards, as this emergency room doctor who has used generative AI explains.
• What to Expect from Generative AI in Analytics and Business Intelligence - Constellation's Doug Henschen turns his attention to AI's impart on analytics, with a visual preview of use cases and some vendor-by-vendor breakdowns.
• Change Management Strategies for Agile Digital Transformations - Eric Kimberling continues his probe of the pros and cons of agile projects: "If it's not an all-or-nothing proposition, you can pick and choose bits and pieces of waterfall, bits and pieces of agile to create the digital transformation strategy and plan that makes the most sense for your organization."
• Forward Thinking on ‘megathreats,’ ‘polycrises,’ and ‘doom loops’ with Nouriel Roubini - This McKinsey podcast (and transcript) puts our current predicaments in perspective.

Whiffs

This is more disconcerting than whiffy, but it reminds us: we better have our BS detectors on:

On the lighter side of disinformation, if there is such a thing:

Another tough reminder: AI advancements cut both ways:

On the other hand, I got this encouraging PR missive:

Maybe things are looking up after all? See you next time... If you find an #ensw piece that qualifies for hits and misses - in a good or bad way - let me know in the comments as Clive (almost) always does. Most Enterprise hits and misses articles are selected from my curated @jonerpnewsfeed.