3 ways AI is Already Transcending Hype and Delivering Tangible Results

3 ways AI is already transcending hype and delivering tangible results

Peter Evans, Xtract One Technologies    in Vneturebeat

@XtractOne, July 15, 2023 8:20 AM

Google search trends for AI have soared since the service launched, and companies are rushing to lap up domains from Anguilla, population 15,000, looking to benefit from its .ai domain registration. 

At the same time, investors are pouring money into generative AI startups, hoping to catch lightning in a bottle and capitalize on this technology to find the next big tech breakthrough. As one AI investor recently told the New York Times, “We’re in that phase of the market where it’s, like, let 1,000 flowers bloom.” 

Today, the hype cycle is so hot that even companies without legitimate AI credentials are trying to align themselves with the technology, prompting the Federal Trade Commission to issue a terse warning to companies: “If you think you can get away with baseless claims that your product is AI-enabled, think again.”

The hype cycle can be so ludicrous that Axios reporter Felix Salmon recently explained, “When a company starts talking loudly about its AI abilities, the first question should always be: “Why is this company talking loudly about its AI abilities?”

To be sure, this isn’t the first rodeo for AI speculation. The technology is more than half a century old, and it’s been through many boom and bust cycles that yielded significant technological advances but have continually failed to fully live up to the hype. 

In other words, developing AI products and services that are repeatable, scalable and sellable has historically been difficult and often prohibitively expensive. However, by looking at the ways AI is already making the most significant impact, we can paint a clearer and possibly more accurate picture of what it will look like moving forward. 

Here are three ways AI is impacting our world today, which can provide a useful roadmap for how it might actually change the world tomorrow.  ...  '

ChatGPT Overhyped? Opinion

Noticed the hype, is it?   Andrew White writes below,  

Artificial IntelligenceChatGPTGPT-3

By Andrew White | January 05, 2023  

I lean toward the hype being overblown.

Pundits are all agog with ChatGPT, language generation tool built using GPT-3. There are examples galore making the social network rounds demonstrating how ChatGPT has rustled up what looks like a sensible response to a question. It seems that the simple questions that stump Alexa every day could be passé, since ChatGPT can handle them all.

In fact, in the WSJ just before Christmas, there was an article titled, “ChatGPT Wrote My AP Essay – and I got a Passing Grade”. The article explains how the author asked ChatGPT to write a 500-word essay on The Great Gatsby. And Lo, the engine did the work and a passing grade was attained. For the press and pundits this was hot news. But is it really?  ... '    More at the link .

IBM, Maersk Pull the Plug on Blockchain-based TradeLens Shipping Platform

Had followed this for some time, I thought it was a good example, used it in talks The 'why' seems weak.  Unless the fundamentals were just not there. 

IBM, Maersk pull the plug on blockchain-based TradeLens shipping platform  By Kyt Dotson in SiliconAngle

Computing giant IBM Corp. and Danish shipping company A.P. Moller – Maersk are discontinuing their blockchain-enabled shipping platform, TradeLens, which was jointly developed by the two companies for tracking shipments and managing supply chains in the container industry.

Maersk announced late Tuesday that the platform had failed to meet its commercial goals necessary to sustain itself, and thus the two companies are now pulling the plug on the platform. It’s expected to go offline by the end of the first quarter of 2023.

“TradeLens was founded on the bold vision to make a leap in global supply chain digitization as an open and neutral industry platform,” said Rotem Hershko, head of business platforms at Maersk. “Unfortunately, while we successfully developed a viable platform, the need for full global industry collaboration has not been achieved.”

TradeLens was launched in 2018 as a collaborative project between the two companies using IBM’s Hyperledger Fabric blockchain technology. It’s used to connect shippers, shipping lines, freight forwarders, port and terminal operators, transportation and customs authorities in order to reduce costs by tracking shipping data and documents.

The objective was to revolutionize the way that documents were transferred between different entities in the supply chain in order to smooth out operations and thus streamline efficiency.   Speaking to SiliconANGLE today, Neeraj Srivastava, co-founder and chief technology officer of DLT Labs, a blockchain firm that develops solutions for fintech and supply chains, argued that TradeLens failed because it spent too much time on hyping itself and too little time on innovation.

“TradeLens’ failure was not that the blockchain wasn’t worthwhile,” said Srivastava. “It’s that it spent too much effort on marketing the platform and hyping up its benefits and not enough time developing the technology to deliver on what the company promised. Too much hype is not good.”

Maersk said it intends to continue efforts to digitize supply chains even after shutting down TradeLens in order to optimize shipping and trade speeds.

Blockchain technology has been tested widely to track and protect supply chains, examples include IBM’s Food Trust Network for food safety, GrainChain for grains and Tradewind Markets Origins for minerals. ... ' 

AI in Medicine Is Overhyped?

 Caution in implementation.

AI in Medicine Is Overhyped? 

By Scientific American, October 25, 2022

Doctor wears virtual reality goggles depicting futuristic healthcare scenario.

Adopting a more holistic approach to developing and testing clinical AI models will lead to more nuanced discussions about how well these models can work and their limitations.

Mistakes by artificial intelligence (AI) models that support doctors’ clinical decisions can mean life or death. Therefore, it is critical that we understand how well these models work before deploying them. Published reports of this technology currently paint a too-optimistic picture of its accuracy, and the scientific papers detailing such advances may become foundations for new companies, new investments and lines of research, and large-scale implementations in hospital systems.

However, in most cases, the technology is not ready for deployment. Why? As researchers feed data into AI models, the models are expected to become more accurate, or at least not get worse. However, our work and the work of others has identified the opposite, where the reported accuracy in published models decreases with increasing dataset size.

From Scientific American

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Quantum Hype

 Much money goes that way ...

Quantum Computer researcher warns that the industry is full of hype ....

"I’M DISTURBED BY SOME OF THE QUANTUM COMPUTING HYPE I SEE THESE DAYS

The nascent field of quantum computing generates a steady drumbeat of attention-grabbing headlines about the looming “quantum apocalypse,” “quantum supremacy,” and endless new investments in ventures that promise to finally crack the commercial capabilities of the tech wide open.

In an excoriating new essay for MIT Tech Review   , though, prominent University of Maryland quantum researcher Sankar Das Sarma says that everybody needs to take a deep, deep breath. .... ' 

Trusting Blockchain

This article was pointed to me by the immediately preceding one,  See also the comments at the link for further debate. 

There's No Good Reason to Trust Blockchain Technology

Bruce Schneier, in Wired, February 6, 2019

In his 2008 white paper that first proposed bitcoin, the anonymous Satoshi Nakamoto concluded with: “We have proposed a system for electronic transactions without relying on trust.” He was referring to blockchain, the system behind bitcoin cryptocurrency. The circumvention of trust is a great promise, but it’s just not true. Yes, bitcoin eliminates certain trusted intermediaries that are inherent in other payment systems like credit cards. But you still have to trust bitcoin—and everything about it.

Much has been written about blockchains and how they displace, reshape, or eliminate trust. But when you analyze both blockchain and trust, you quickly realize that there is much more hype than value. Blockchain solutions are often much worse than what they replace.  .... ' 

A Look at Blockchain Hype

Good somewhat technical examination of work underway, including work by IBM, Hyperledger and hype of this space in general. 

Blockchain For What, Exactly?  By Doug Meil   in CACM   February 4, 2022

Blockchain is built upon multiple previously established technologies and techniques, such as consensus protocols and append-only data structures. Nearly everyone at this point should know that cryptocurrencies today run on blockchain, but not all blockchains need be cryptocurrencies. Which raises the question about what precisely blockchain can be used for in the non-cryptocurrency use-case, and according to some, the answer is "everything."

Every new technology has a hype cycle, but blockchain's hype cycle has an amplitude that few technologies have matched. Unfortunately, the lion's share of misunderstanding about blockchain has come from within its own community. It didn't have to be like this.

IBM, Blockchain, and Healthcare

IBM has been loathe to miss a hype-cycle, and it did not disappoint with blockchain. For example, in a January 2017 article titled "IBM Watson, FDA aim to tackle, tame blockchain for data exchange," an IBM executive said:

"Blockchain technology has advanced and has matured.  At the core, this technology can address various frictions in the health system, such as meaningful collaboration and coordination in healthcare that require addressing privacy concerns, lack of interoperability, and the issue of trustworthiness of data."

… and then went on to also say …

"For providers it can provide the continuity of the health record and the longitudinal 360 view of the patient that the providers need in order to provide the health services to the patient."

I have emphasized certain words in the quotations, as the phrases "privacy concerns," "continuity of the health record," and "longitudinal 360 view of the patient" mean specific things in healthcare. Yet how blockchain would specifically address those points is never made clear.

The reason this specific article is so personally important is that I had to respond to a customer about it back when I was at IBM Watson Health.  One of our unit's (healthcare) customers saw the story and wondered what these words meant for them, and wondered and worried if their data was going to wind up on a blockchain. I had to start learning about blockchain defensively, and the task was made more complicated because IBM's Blockchain group couldn't explain any of the claims in the article. I started reading about Hyperledger, a blockchain framework favored by IBM for private blockchain use-cases.

Consider the following high-level blockchain architecture diagram from the Hyperledger project, with respect to key questions that I typically don't see addressed well enough with private blockchain use-cases:  .... ' 

Sciam Says Self Driving Cars Emergent

Scientific American takes a look at a self driving future

'Self-Driving' Cars Begin to Emerge from a Cloud of Hype    By Scientific American, September 27, 2021

Although some observers may perceive that the bloom is off the rose for automated driving in this post-hype environment, the current situation actually marks a sign of progress. More realistic views of the opportunities and challenges for automated driving will motivate better-focused investment of resources and alignment of public perceptions with reality.

We should expect some limited implementations of automated long-haul trucking on low-density, rural highways and automated local small-package delivery in urban and suburban settings during the current decade. Automated urban and suburban ride-hailing services could become available on a limited basis as well, but the location-specific challenges to their deployment are sufficient that this is unlikely to reach a national scale soon.

From Scientific American 

Combatting Technology Hype

Back to  measures and risks,  often economical.    And then their reasonable forward prediction.

Issues in Science and Technology
Combatting Tech Hype

VOL. XXXVI, NO. 2, WINTER 2020

By BRENT GOLDFARB, DAVID A. KIRSCH, CARLOTA PEREZ, MARTIN KENNEY ...

We enjoyed Jeffrey Funk’s “What’s Behind Technological Hype?” (Issues, Fall 2019). However, as authors of a recent book on financial speculation arising from the commercialization of new technology, Bubbles and Crashes: The Boom and Bust of Technological Innovation (Stanford, 2019), we take issue with a few of Funk’s interpretations.

First, Funk points in several instances to the “lack of good economic analysis” as a critical factor leading to hype. However, what’s really needed is different economic analysis. Understanding technology calls for economic analysis that engages what Robert Shiller called “narrative economics.” Traditional economic approaches are not much help when confronting the fundamental uncertainty that arises from the introduction and potential adoption of a new technology or system. To understand choices at that margin, we need to be sensitive to the sources and impacts of narratives. Narratives are a double-edged sword: carefully deployed, they can coordinate collective action and funnel resources into risky but ultimately profitable ventures, but narratives can also lead to hype, speculation, and damaging bubbles. Unfortunately, in spite of Shiller’s call to action, most economists would not recognize the study of narratives as central to the study of booms and busts, so we need more than “good” economic analysis.

Second, once we accept the intractability of uncertainty, it is not realistic to expect to be able to entirely soften the blow of failure. Indeed, failure may be good, and not in some milquetoast, learning-from-failure way. Awful, terrible, value-destroying failure is good because it signals that our local instance of late-entrepreneurial capitalism is still capable of taking big risks. The implications of this logic are far-reaching: what if the risk that we stop failing (because we stop placing big, transformational bets) is more dangerous than the cost of a little too much hype? This is a hard question to answer, partly because the costs and benefits are incommensurable and partly because they accumulate across time in messy, discontinuous ways. From our perspective, the critical issue is not minimizing failure, but maximizing the categories and numbers of people who can afford to fail. Unfortunately, recent macroeconomic developments suggest that we are doing little to redress the “Lost Einsteins” problem, thereby losing even more of the bold, if risky, ideas that we need in order to support meaningful economic experimentation.

A more critical, narrative economic analysis would focus on how much of the imagined future builds on only imagined elements of the new technological system. Knowing how much is imagined might counteract hype that glosses over these elements.

Brent Goldfarb   Associate Professor
David A. Kirsch Associate Professor    Robert H. Smith School of Business   University of Maryland

On the Cusp of an AI Winter?

We have done lots of new things like better language skills and pattern recognition.  But we have fallen back on delivering real process intelligence.    Circa 1990, the last 'winter' created a stall that lasted some 20 years.   Hype over the meaning of the word 'intelligence '?   Expectation to readily clone the working of the brain?  Are we ready for the next winter? 

What might save us from that winter?  Better yet integration of RPA process intelligence with BPM? Deeper language understanding.  Deeper and better contextual intelligence?   We need something.

Researchers: Are We on the Cusp of an ‘AI Winter’   By BBC.com

Artificial intelligence researchers believe their industry is about to enter a new phase.

The last decade was a big one for artificial intelligence, but researchers in the field believe that the industry is about to enter a new phase.

Hype surrounding AI has peaked and troughed over the years as the abilities of the technology get overestimated and then re-evaluated.

The peaks are known as AI summers, and the troughs AI winters.   The 10s were arguably the hottest AI summer on record with tech giants repeatedly touting AI's abilities.

AI pioneer Yoshua Bengio, sometimes called one of the "godfathers of AI," told the BBC that AI's abilities were somewhat overhyped in the 10s by certain companies with an interest in doing so.

There are signs, however, that the hype might be about to start cooling off.

From BBC.com ... "

Quantum Bull

So is Quantum her already, or are we in the midst of a hype storm?    Check out the links below and explore.   A number of technical big players are participating ... so can it be purely nonsense?  Not likely.  But exactly what it can do versus just rumored to do soon is still unclear.

 Revolt! Scientists Say They're Sick of Quantum Computing's Hype
A Twitter account called Quantum Bullshit Detector reflects some researchers' angst about overhyped claims and other troubling trends.

This spring, a mysterious figure by the name of Quantum Bullshit Detector strolled onto the Twitter scene. Posting anonymously, they began to comment on purported breakthroughs in quantum computing—claims that the technology will speed up artificial intelligence algorithms, manage financial risk at banks, and break all encryption. The account preferred to express its opinions with a single word: “Bullshit.”

The provocations perplexed experts in the field. Because of the detector’s familiarity with jargon and the accounts it chose to follow, the person or persons behind the account seemed be part of the quantum community. Researchers were unaccustomed to such brazen trolling from someone in their own ranks. “So far it looks pretty well-calibrated, but [...] vigilante justice is a high-risk affair,” physicist Scott Aaronson wrote on his blog a month after the detector’s debut. People discussed online whether to take the account’s opinions seriously.

“There is some confusion. Quantum Bullshit Detector cannot debate you. It can only detect quantum bullshit. This is why we are Quantum Bullshit Detector!” the account tweeted in response. ... " 

AI is not An Excuse

Internet founder Vint Cerf does a good job putting out a cautious view on the current use of AI.  In theory good research, development and value should never be replaced by emergent Hype.    But in reality research groups, enterprises and startups have limited funds, and they will spend significantly on potential big wins or benefits.  However risky.  And in the case of current AI results, they solve previously unsolvable problems,  so the bait is out there.   So be cautious, arm yourself with as much information and experience as possible, prototype and aim for real value.  Don't wait for AI or something like it. 

AI Is Not an Excuse!  By Vinton G. Cerf

Communications of the ACM, October 2019, Vol. 62 No. 10, Page 7

I keep hearing excuses for not working on difficult problems: "Eventually AI will solve this so there's no point working on it now." Sorry, wrong answer.

First, we should be cautious about putting too much expectation on artificial intelligence which, by most metrics, is really today's machine learning (ML) and neural networks. There is no doubt these systems have produced truly remarkable results. The GO game story of AlphaGo and AlphaZero from Deep Mind is by now a classic example of the surprisingly powerful results these systems produce. A chess-playing version of AlphaZero learned quickly and demonstrated choices of moves unlike those of traditional chess players. I hesitate to label this strategy but the deep neural networks do encode in some deep way experience that one could consider a kind of strategic cache.  .... " 

The AI Work of the Future Report

Having been seeing the AI hype of late, and getting questions from colleagues and clients as to that tt really means.  This piece from MIT, pointed to by O'Reilly, is refreshing in that addresses what still cannot be done, needs to be addressed.   Their "Work of the Future Report: Shaping Technologies and Futures".

I am a big proponent and optimist on the topic, but still think we need to know what the unsolved challenges still are.   And make plans as to what we need to do to solve them.   Both by the scientists and by the business decision makers and process inventors.   Do read this report.

Cutting Through 5G Hype

Seems to be a major issue, especially with regard to how smart homes, and connected automobiles will be implemented.  McKinsey reports on the hype, with predictions about what we might get when:

" .... Cutting through the 5G hype: Survey shows telcos’ nuanced views

Operators see a marginally positive business case, expect rollout at scale to take until 2022, and don’t think the increase in capital-expense-to-sales ratio will be as big as skeptics claim.  ... " 

Ditch the term Blockchain?

I agree, when hype exceeds reality you have to take great care.  Start with a good business case.

Via Fortune, a short talk by execs.

Time to Ditch the Word 'Blockchain', Report Says

A new report from Forrester Research says the buzz around blockchain, a technology that creates tamper-proof records across multiple computers, is so over-hyped that some companies are dropping the word altogether.

According to Forrester, firms are ditching the b-word in favor of “DLT,” which is shorthand for distributed ledger technology—a more descriptive, if less catchy, term.

The report comes at a time when blockchain marketing is everywhere, including during the recent World Series, when IBM touted its blockchain services in TV commercials.
While blockchain is an important new technology, some firms are over-hyping its usefulness or simply repackaging existing services—a practice the report, which endorses the use of “DLT,” describes as “blockchain washing.”

“The networks that are live or under development vary greatly and frequently lack key characteristics that many regard as essential components of a blockchain,” the report states, adding the term blockchain can also carry negative “wild west connotations” of cryptocurrency.  ... " ... '

AI Overhyped? The Term is.

The problem is the term AI itself.   The assumption that it is far more than it is.   This does not mean you should not think about how smarter capabilities could be inserted into codes to augment our capabilities.  For a while we were using the term 'Cognitive Systems' to indicate methods closer and even mimicking human perception and abilities.  Probably be better to ditch 'AI' and go with Cognitive.  Though even the latter requires too much explanation and can be over emphasized.   Our Cognitive Systems Institute, monitored here,  attempts to emphasize cognitive aspects. Beware over-marketing.

 Artificial intelligence is often overhyped—and here’s why that’s dangerous

AI has huge potential to transform our lives, but the term itself is being abused in very worrying ways, says Zachary Lipton, an assistant professor at Carnegie Mellon University.
by Martin Giles

To those with long memories, the hype surrounding artificial intelligence is becoming ever more reminiscent of the dot-com boom.

Billions of dollars are being invested into AI startups and AI projects at giant companies. The trouble, says Zachary Lipton, is that the opportunity is being overshadowed by opportunists making overblown claims about the technology’s capabilities.

During a talk at MIT Technology Review’s EmTech conference today, Lipton warned that the hype is blinding people to its limitations. “It’s getting harder and harder to distinguish what’s a real advance and what is snake oil,” he said.

AI technology known as deep learning has proved very powerful at performing tasks like image recognition and voice translation, and it’s now helping to power everything from self-driving cars to translation apps on smartphones,

But the technology still has significant limitations. Many deep-learning models only work well when fed vast amounts of data, and they often struggle to adapt to fast-changing real-world conditions.

In his presentation, Lipton also highlighted the tendency of AI boosters to claim human-like capabilities for the technology. The risk is that the AI bubble will lead people to place too much faith in algorithms governing things like autonomous vehicles and clinical diagnoses.

“Policymakers don’t read the scientific literature,” warned Lipton, “but they do read the clickbait that goes around.” The media business, he says, is complicit here because it’s not doing a good enough job of distinguishing between real advances in the field and PR fluff.

Lipton isn’t the only academic sounding the alarm: in a recent blog post, “Artificial Intelligence—The Revolution Hasn’t Happened Yet,” Michael Jordan, a professor at University of California, Berkeley, says that AI is all too often bandied about as “an intellectual wildcard,” and this makes it harder to think critically about the technology’s potential impact. ... " 

AI Winter?

Some of us are afraid to ask, but O'Reilly brings it up and points to evidence.  My team wintered the last one, and it was not pretty.  Its not that we didn't achieve much, we produced millions for the enterprise.  But it just did not prevail despite all the advances we made, both in investments and training human resources.  Hype drove it then, helped and hindered regarding expectations.  That is surely happening again.   But we are too harvesting advances in areas like machine learning that will not go away.

O'Reilly Asks:

Are we heading into another AI winter?
It's happened before, and murmurs of another AI winter coming are increasing: see Filip Piekniewski, Ronald Schmelzer, and Eleanor Cummins. Certainly, the AI hype is starting to get stale, and signs are that several AI technologies are at their peak of inflated expectations and quickly headed for the trough of disillusionment. But this excellent post by Michael Jordan (which we've pointed to in an earlier issue), looks at the question a little differently. Has AI spring arrived yet? ... " 

And they point to an article: 

By:  Michael I. Jordan who is a Professor in the Department of Electrical Engineering and Computer Sciences and the Department of Statistics at UC Berkeley. ... 

Artificial Intelligence — The Revolution Hasn’t Happened Yet
Artificial Intelligence (AI) is the mantra of the current era. The phrase is intoned by technologists, academicians, journalists and venture capitalists alike. As with many phrases that cross over from technical academic fields into general circulation, there is significant misunderstanding accompanying the use of the phrase. But this is not the classical case of the public not understanding the scientists — here the scientists are often as befuddled as the public. The idea that our era is somehow seeing the emergence of an intelligence in silicon that rivals our own entertains all of us — enthralling us and frightening us in equal measure. And, unfortunately, it distracts us.  ... "

BlockChain Strategic Business Value

Good, considerable piece in McKinsey.  A number of useful but general industry postionings and examples.  Just a bare mention of definition of smart contracts and their current limitations. 

Blockchain beyond the hype: What is the strategic business value?  in McKinsey   By Brant Carson, Giulio Romanelli, Patricia Walsh, and Askhat Zhumaev

Companies can determine whether they should invest in blockchain by focusing on specific use cases and their market position. .... "

WEF: Cutting Through Blockchain Hype

 Useful reports and discussion from the World Economic Forum (WEF).

Blockchain Beyond the Hype

This common sense and practical framework is designed to assist executives in understanding whether blockchain is an appropriate and helpful tool for their business needs. It starts from the premise that blockchain is merely a technology – much like many others that are already used in society – and like other technologies it is as much about change management and careful attention to the economics and business models of industries and companies involved as it is about technology evangelism. For any organization, blockchain technology should not be a goal in itself but a tool deployed to achieve specific purposes.

This toolkit is based on real-world experience of blockchain in a variety of projects across a variety of industries that have been analysed by Imperial College London to develop an initial framework. The framework has been reviewed and further developed by members of the 2017 World Economic Forum’s Global Future Council on Blockchain and has been trialed through a variety of means, including with global chief executive officers (CEOs) at the World Economic Forum Annual Meeting 2018 in Davos-Klosters. Over the coming months, the World Economic Forum’s Center for the Fourth Industrial Revolution, in partnership with various institutions, will be releasing customized versions of this toolkit focused on specific sectors and use cases.  ... "

White Paper 23 April 2018   Download PDF  Full image in white paper.

And below from their Blockchain Toolkit:

(Click to Enlarge)

Defining Blockchain

Bad and misleading, certainly inconsistent terminology leads to raving hype?  And don't expect the current definitions to survive.   This piece in The Verge makes the case well.      ‘Blockchain is Meaningless’    ‘You keep using that word. I do not think it means what you think it means’
By Adrianne Jeffries  @adrjeffries