Big Plays or Little Plays: The Key to AI Revenue

July 11, 2024

I keep thinking about the billions and trillions of dollars required to create a big AI win. A couple of snappy investment banks have edged toward the idea that AI might not pay off with tsunamis of money right away. The fix is to become brokers for GPU cycles or “humble brags” about how more money is needed to fund the next big thing in what venture people want to be the next big thing. Yep, AI: A couple of winners and the rest are losers at least in terms of the pay off scale whacked around like a hapless squash ball at the New York Athletic Club.

However, a radical idea struck me as I read a report from the news service that oozes “trust.” The Reuters’ story is “China Leads the World in Adoption of Generative AI Survey Shows.” Do I trust surveys? Not really. Do I trust trusted “real” news outfits? Nope, not really. But the write up includes an interesting statement, and the report sparked what is for me a new idea.

First, here’s the passage I circled:

“Enterprise adoption of generative AI in China is expected to accelerate as a price war is likely to further reduce the cost of large language model services for businesses. The SAS report also said China led the world in continuous automated monitoring (CAM), which it described as “a controversial but widely-deployed use case for generative AI tools”.”

I interpreted this to mean:

  • Small and big uses of AI in somewhat mundane tasks
  • Lots of small uses with more big outfits getting with the AI program
  • AI allows nifty monitoring which is going to catch the attention of some Chinese government officials who may be able to repurpose these focused applications of smart software

With models available as open source like the nifty Meta Facebook Zuck concoction, big technology is available. Furthermore the idea of applying smart software to small problems makes sense. The approach avoids the Godzilla lumbering associated with some outfits and, second, fast iteration with fast failures provides useful factoids for other developers.

The “real” news report does not provide numbers or much in the way of analysis. I think the idea of small-scale applications does not make sense when one is eating fancy food at a smart software briefing in mid town Manhattan. Small is not going to generate that. big wave of money from AI. The money is needed to raise more money.

My thought is that the Chinese approach has value because it is surfing on open source and some proprietary information known to Chinese companies solving or trying to solve a narrow problem. Also, the crazy pace of try-fail, try-fail enables acceleration of what works. Failures translate to lessons about what lousy path to follow.

Therefore, my reaction to the “real” news about the survey is that China may be in a position to do better, faster, and cheaper AI applications that the Godzilla outfits. The chase for big money exists, but in the US without big money, who cares? In China, big money may not be as large as the pile of cash some VCs and entrepreneurs argue is absolutely necessary.

So what? The “let many flowers bloom” idea applies to AI. That’s a strength possibly neither appreciated or desired by the US AI crowd. Combined with China’s patent surge, my new thought translates to “oh, oh.”

Stephen E Arnold, July 11, 2024

Common Sense from an AI-Centric Outfit: How Refreshing

July 11, 2024

green-dino_thumb_thumb_thumb_thumb_tThis essay is the work of a dumb dinobaby. No smart software required.

In the wild and wonderful world of smart software, common sense is often tucked beneath a stack of PowerPoint decks and vaporized in jargon-spouting experts in artificial intelligence. I want to highlight “Interview: Nvidia on AI Workloads and Their Impacts on Data Storage.” An Nvidia poohbah named Charlie Boyle output some information that is often ignored by quite a few of those riding the AI pony to the pot of gold at the end of the AI rainbow.


The King Arthur of senior executives is confident that in his domain he is the master of his information. By the way, this person has an MBA, a law degree, and a CPA certification. His name is Sir Walter Mitty of Dorksford, near Swindon. Thanks, MSFT Copilot.  Good enough.

Here’s the pivotal statement in the interview:

… a big part of AI for enterprise is understanding the data you have.

Yes, the dwellers in carpetland typically operate with some King Arthur type myths galloping around the castle walls; specifically:

Myth 1: We have excellent data

Myth 2: We have a great deal of data and more arriving every minute our systems are online

Myth 3: Out data are available and in just a few formats. Processing the information is going to be pretty easy.

Myth 4: Out IT team can handle most of the data work. We may not need any outside assistance for our AI project.

Will companies map these myths to their reality? Nope.

The Nvidia expert points out:

…there’s a ton of ready-made AI applications that you just need to add your data to.

“Ready made”: Just like a Betty Crocker cake mix my grandmother thought tasted fake, not as good as home made. Granny’s comment could be applied to some of the AI tests my team have tracked; for example, the Big Apple’s chatbot outputting  comments which violated city laws or the exciting McDonald’s smart ordering system. Sure, I like bacon on my on-again, off-again soft serve frozen dessert. Doesn’t everyone?

The Nvidia experts offers this comment about storage:

If it’s a large model you’re training from scratch you need very fast storage because a lot of the way AI training works is they all hit the same file at the same time because everything’s done in parallel. That requires very fast storage, very fast retrieval.

Is that a problem? Nope. Just crank up the cloud options. No big deal, except it is. There are costs and time to consider. But otherwise this is no big deal.

The article contains one gems and wanders into marketing “don’t worry” territory.

From my point of view, the data issue is the big deal. Bad, stale, incomplete, and information in odd ball formats — these exist in organizations now. The mass of data may have 40 percent or more which has never been accessed. Other data are back ups which contain versions of files with errors, copyright protected data, and Boy Scout trip plans. (Yep, non work information on “work” systems.)

Net net: The data issue is an important one to consider before getting into the let’s deploy a customer support smart chatbot. Will carpetland dwellers focus on the first step? Not too often. That’s why some AI projects get lost or just succumb to rising, uncontrollable costs. Moving data? No problem. Bad data? No problem. Useful AI system? Hmmm. How much does storage cost anyway? Oh, not much.

Stephen E Arnold, July 11, 2024

Microsoft Security: Big and Money Explain Some Things

July 10, 2024

I am heading out for a couple of day. I spotted this story in my newsfeed: “The President Ordered a Board to Probe a Massive Russian Cyberattack. It Never Did.” The main point of the write up, in my opinion, is captured in this statement:

The tech company’s failure to act reflected a corporate culture that prioritized profit over security and left the U.S. government vulnerable, a whistleblower said.

But there is another issue in the write up. I think it is:

The president issued an executive order establishing the Cyber Safety  Review Board in May 2021 and ordered it to start work by reviewing the SolarWinds attack. But for reasons that experts say remain unclear, that never happened.

The one-two punch may help explain why some in other countries do not trust Microsoft, the US government, and the cultural forces in the US of A.

Let’s think about these three issues briefly.


A group of tomorrow’s leaders responding to their teacher’s request to pay attention and do what she is asking. One student expresses the group’s viewpoint. Thanks, MSFT Copilot. How the Recall today? What about those iPhones Mr. Ballmer disdained?

First, large technology companies use the word “trust”; for example, Microsoft apparently does not trust Android devices. On the other hand, China does not have trust in some Microsoft products. Can one trust Microsoft’s security methods? For some, trust has become a bit like artificial intelligence. The words do not mean much of anything.

Second, Microsoft, like other big outfits needs big money. The easiest way to free up money is to not spend it. One can talk about investing in security and making security Job One. The reality is that talk is cheap. Cutting corners seems to be a popular concept in some corporate circles. One recent example is Boeing dodging trials with a deal. Why? Money maybe?

Third, the committee charged with looking into SolarWinds did not. For a couple of years after the breach became known, my SolarWinds’ misstep analysis was popular among some cyber investigators. I was one of the few people reviewing the “misstep.”

Okay, enough thinking.

The SolarWinds’ matter, the push for money and more money, and the failure of a committee to do what it was asked to do explicitly three times suggests:

  1. A need for enforcement with teeth and consequences is warranted
  2. Tougher procurement policies are necessary with parallel restrictions on lobbying which one of my clients called “the real business of Washington”
  3. Ostracism of those who do not follow requests from the White House or designated senior officials.

Enough of this high-vulnerability decision making. The problem is that as I have witnessed in my work in Washington for decades, the system births, abets, and provides the environment for doing what is often the “wrong” thing.

There you go.

Stephen E Arnold, July 10, 2024

Market Research Shortcut: Fake Users Creating Fake Data

July 10, 2024

Market research can be complex and time consuming. It would save so much time if one could consolidate thousands of potential respondents into one model. A young AI firm offers exactly that, we learn from Nielsen Norman Group’s article, “Synthetic Users: If, When, and How to Use AI Generated ‘Research.’

But are the results accurate? Not so much, according to writers Maria Rosala and Kate Moran. The pair tested fake users from the young firm Synthetic Users and ones they created using ChatGPT. They compared responses to sample questions from both real and fake humans. Each group gave markedly different responses. The write-up notes:

“The large discrepancy between what real and synthetic users told us in these two examples is due to two factors:

  • Human behavior is complex and context-dependent. Synthetic users miss this complexity. The synthetic users generated across multiple studies seem one-dimensional. They feel like a flat approximation of the experiences of tens of thousands of people, because they are.
  • Responses are based on training data that you can’t control. Even though there may be proof that something is good for you, it doesn’t mean that you’ll use it. In the discussion-forum example, there’s a lot of academic literature on the benefits of discussion forums on online learning and it is possible that the AI has based its response on it. However, that does not make it an accurate representation of real humans who use those products.”

That seems obvious to us, but apparently some people need to be told. The lure of fast and easy results is strong. See the article for more observations. Here are a couple worth noting:

“Real people care about some things more than others. Synthetic users seem to care about everything. This is not helpful for feature prioritization or persona creation. In addition, the factors are too shallow to be useful.”


“Some UX [user experience] and product professionals are turning to synthetic users to validate or product concepts or solution ideas. Synthetic Users offers the ability to run a concept test: you describe a potential solution and have your synthetic users respond to it. This is incredibly risky. (Validating concepts in this way is risky even with human participants, but even worse with AI.) Since AI loves to please, every idea is often seen as a good one.”

So as appealing as this shortcut may be, it is a fast track to incorrect results. Basing business decisions on “insights” from shallow, eager-to-please algorithms is unwise. The authors interviewed Synthetic Users’ cofounder Hugo Alves. He acknowledged the tools should only be used as a supplement to surveys of actual humans. However, the post points out, the company’s website seems to imply otherwise: it promises “User research. Without the users.” That is misleading, at best.

Cynthia Murrell, July 10, 2024

TV Pursues Nichification or 1 + 1 = Barrels of Money

July 10, 2024

green-dino_thumb_thumb_thumb_thumb_t_thumbThis essay is the work of a dumb dinobaby. No smart software required.

When an organization has a huge market like the Boy Scouts and the Girl Scouts? What do they do to remain relevant and have enough money to pay the overhead and salaries of the top dogs? They merge.

What does an old-school talking heads television channel do to remain relevant and have enough money to pay the overhead and salaries of the top dogs? They create niches.


A cheese maker who can’t sell his cheddar does some MBA-type thinking. Will his niche play work? Thanks, MSFT Copilot. How’s that Windows 11 update doing today?

Which path is the optimal one? I certainly don’t have a definitive answer. But if each “niche” is a new product, I remember hearing that the failure rate was of sufficient magnitude to make me a think in terms of a regular job. Call me risk averse, but I prefer the rational dinobaby moniker, thank you.

CNBC Launches Sports Vertical amid Broader Biz Shift” reports with “real” news seriousness:

The idea is to give sports business executives insights and reporting about sports similar to the data and analysis CNBC provides to financial professionals, CNBC President KC Sullivan said in a statement.

I admit. I am not a sports enthusiast. I know some people who are, but their love of sport is defined by gambling, gambling and drinking at the 19th hole, and dressing up in Little League outfits and hitting softballs in the Harrod’s Creek Park. Exciting.

The write up held one differentiator from the other seemingly endless sports programs like those featuring Pat McAfee-type personalities. Here’s the pivot upon which the nichification turns:

The idea is to give sports business executives insights and reporting about sports similar to the data and analysis CNBC provides to financial professionals…

Imagine the legions of viewers who are interested in dropping billions on a major sports franchise. For me, it is easier to visualize sports betting. One benefit of gambling is a source of “addicts” for rehabilitation centers.

I liked the wrap up for the article. Here it is:

Between the lines: CNBC has already been investing in live coverage of sports, and will double down as part of the new strategy.

  • CNBC produces an annual business of sports conference, Game Plan, in partnership with Boardroom.
  • Andrew Ross Sorkin, Carl Quintanilla and others will host coverage from the 2024 Olympic Games in Paris this summer.

Zoom out: Cable news companies are scrambling to reimagine their businesses for a digital future.

  • CNBC already sells digital subscriptions that include access to its live TV feed.
  • In the future, it could charge professionals for niche insights around specific verticals, or beats.

Okay, I like the double down, a gambling term. I like the conference angle, but the named entities do not resonate with me. I am a dinobaby and nichification is not a tactic that an outfit with eyeballs going elsewhere makes sense to me. The subscription idea is common. Isn’t there something called “subscription fatigue”? And the plan to charge to access a sports portal is an interesting one. But if one has 1,000 people looking at content, the number who subscribe seems to be in the < one to two percent range based on my experience.

But what do I know? I am a dinobaby and I know about TikTok and other short form programming. Maybe that’s old hat too? Did CNBC talk to influencers?

Stephen E Arnold, July 10, 2024

A Signal That Money People Are Really Worried about AI Payoffs

July 8, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

AI’s $600B Question” is an interesting signal. The subtitle for the article is the pitch that sent my signal processor crazy: The AI bubble is reaching a tipping point. Navigating what comes next will be essential.”


Executives on a thrill ride seem to be questioning the wisdom of hopping on the roller coaster. Thanks, MSFT Copilot. Good enough.

When money people output information that raises a question, something is happening. When the payoff is nailed, the financial types think about yachts, Bugatti’s, and getting quoted in the Financial Times. Doubts are raised because of these headline items: AI and $600 billion.

The write up says:

A huge amount of economic value is going to be created by AI. Company builders focused on delivering value to end users will be rewarded handsomely. We are living through what has the potential to be a generation-defining technology wave. Companies like Nvidia deserve enormous credit for the role they’ve played in enabling this transition, and are likely to play a critical role in the ecosystem for a long time to come. Speculative frenzies are part of technology, and so they are not something to be afraid of.

If I understand this money talk, a big time outfit is directly addressing fears that AI won’t generate enough cash to pay its bills and make the investors a bundle of money. If the AI frenzy was on the Money Train Express, why raise questions and provide information about the tough-to-control costs for making AI knock off the hallucination, the product recalls, the lawsuits, and the growing number of AI projects which just don’t work?

The fact of the article’s existence makes it clear to me that some folks are indeed worried. Does the write up reassure those with big bucks on the line? Does the write up encourage investors to pump more money into a new AI start up? Does the write up convert tests into long-term contracts with the big AI providers?

Nope, nope, and nope.

But here’s the unnerving part of the essay:

In reality, the road ahead is going to be a long one. It will have ups and downs. But almost certainly it will be worthwhile.

Translation: We will take your money and invest it. Just buckle up, butter cup. The ride on this roller coaster may end with the expensive cart hurtling from the track to the asphalt below. But don’t worry about us venture types. We will surf on churn and the flows of money. Others? Not so much.

Stephen E Arnold, July 8, 2024

Happy Fourth of July Says Microsoft to Some Employees

July 8, 2024

dinosaur30a_thumb_thumb_thumbThis essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.

I read “Microsoft Lays Off Employees in New Round of Cuts.” The write up reports:

Microsoft conducted another round of layoffs this week in the latest workforce reduction implemented by the Redmond tech giant this year… Posts on LinkedIn from impacted employees show the cuts affecting employees in product and program management roles.

I wonder if some of those Softies were working on security (the new Job One at Microsoft) or the brilliantly conceived and orchestrated Recall “solution.”

The write up explains or articulates an apologia too:

The cutbacks come as Microsoft tries to maintain its profit margins amid heavier capital spending, which is designed to provide the cloud infrastructure needed to train and deploy the models that power AI applications.

Several observations:

  1. A sure-fire way to solve personnel and some types of financial issues is identifying employees, whipping up some criteria-based dot points, and telling the folks, “Good news. You can find your future elsewhere.”
  2. Dumping people calls attention to management’s failure to keep staff and tasks aligned. Based on security and reliability issues Microsoft evidences, the company is too large to know what color sock is on each foot.
  3. Microsoft faces a challenge, and it is not AI. With more functions working in a browser, perhaps fed up individuals and organizations will re-visit Linux as an alternative to Microsoft’s products  and services?

Net net: Maybe firing the security professionals and those responsible for updates which kill Windows machines is a great idea?

Stephen E Arnold, July 8, 2024

VPNs, Snake Oil, and Privacy

July 2, 2024

dinosaur30a_thumb_thumb_thumb_thumb_thumb_thumbThis essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.

Earlier this year, I had occasion to meet a wild and crazy entrepreneur who told me that he had the next big thing in virtual private networks. I listened to the words and tried to convert the brightly-covered verbal storm into something I could understand. I failed. The VPN, as I recall the energizer bunny powered start up impresario needed to be reinvented.

6 28 how this for a diagram


I knew that the individual’s knowledge of VPNs was — how shall I phrase it — limited. As an educational outreach, I forwarded to the person who wants to be really, really rich the article “Novel Attack against Virtually All VPN Apps Neuters Their Entire Purpose.” The write up focuses on an exploit which compromises the “secrecy” the VPN user desires. I hopes the serial entrepreneur notes this passage:

“The attacker can read, drop or modify the leaked traffic and the victim maintains their connection to both the VPN and the Internet.”

Technical know how is required, but the point is that VPNs are often designed to:

  1. Capture data about the VPN user and other quite interesting metadata. These data are then used either for marketing, search engine optimization, or simple information monitoring.
  2. A way to get from a VPN hungry customer a credit card which can be billed every month for a long, long time. The customer believes a VPN adds security when zipping around from Web site to online service. Ignorance is bliss, and these VPN customers are usually happy.
  3. A large-scale industrial operation which sells VPN services to repackagers who buy bulk VPN bandwidth and sell it high. The winner is the “enabler” or specialized hosting provider who delivers a vanilla VPN service on the cheap and ignores what the resellers say and do. At one of the law enforcement / intel conferences I attended I heard someone mention the name of an ISP in Romania. I think the name of this outfit was M247 or something similar. Is this a large scale VPN utility? I don’t know, but I may take a closer look because Romania is an interesting country with some interesting online influencers who are often in the news.

The write up includes quite a bit of technical detail. There is one interesting factoid that took care to highlight for the VPN oriented entrepreneur:

Interestingly, Android is the only operating system that fully immunizes VPN apps from the attack because it doesn’t implement option 121. For all other OSes, there are no complete fixes. When apps run on Linux there’s a setting that minimizes the effects, but even then TunnelVision can be used to exploit a side channel that can be used to de-anonymize destination traffic and perform targeted denial-of-service attacks. Network firewalls can also be configured to deny inbound and outbound traffic to and from the physical interface. This remedy is problematic for two reasons: (1) a VPN user connecting to an untrusted network has no ability to control the firewall and (2) it opens the same side channel present with the Linux mitigation. The most effective fixes are to run the VPN inside of a virtual machine whose network adapter isn’t in bridged mode or to connect the VPN to the Internet through the Wi-Fi network of a cellular device.

What’s this mean? In a nutshell, Google did something helpful. By design or by accident? I don’t know. You pick the option that matches your perception of the Android mobile operating system.

This passage includes one of those observations which could be helpful to the aspiring bad actor. Run the VPN inside of a virtual machine and connect to Internet via a Wi-Fi network or mobile cellular service.

Several observations are warranted:

  1. The idea of a “private network” is not new. A good question to pose is, “Is there a way to create a private network that cannot be detected using conventional traffic monitoring and sniffing tools? Could that be the next big thing for some online services designed for bad actors?
  2. The lack of knowledge about VPNs makes it possible for data harvesters and worse to offer free or low cost VPN service and bilk some customers out of their credit card data and money.
  3. Bad actors are — at some point — going to invest time, money, and programming resources in developing a method to leapfrog the venerable and vulnerable VPN. When that happens, excitement will ensue.

Net net: Is there a solution to VPN trickery? Sure, but that involves many moving parts. I am not holding my breath.

Stephen E Arnold, July 2, 2024

Will Google Charge for AI Features? Of Course

July 2, 2024

Will AI spur Google to branch out from its ad-revenue business model? Possibly, Dataconomy concludes in, “AI Is Draining Google’s Money and We May Be Charged for It.” Writer Eray Eliaç?k cites reporting from the Financial Times when stating:

“Google, the search engine used by billions, is considering charging for special features made possible by artificial intelligence (AI). This would be different from its usual practice of offering most of its services for free. Here’s what this could mean: Google might offer some cool AI-driven tools, like a smarter assistant or personalized search options, but only to those who pay for them. The regular Google search would stay free, but these extra features would come with a price tag, such as Gemini, SGE, and Image generation with AI and more.”

Would Google really make more charging for AI than on serving up ads alongside it? Perhaps it will do both?

Eliaç?k reminds us AI is still far from perfect. There are several reasons he does not address:

  1. Google faces a challenge to maintain its ad monopolies as investigations into its advertising business which has been running without interference for more than two decades
  2. AI is likely to be a sector with a big dog and a couple of mid sized dogs, and a bunch of French bulldogs (over valued and stubborn). Google wants to be the winner because it invented the transformer and now has to deal with the consequences of that decision. Some of the pretenders are likely to be really big dogs and capable of tearing off Googzilla’s tail
  3. Cost control is easy to talk about in MBA class and financial columns. In real online life, cost control is a thorny problem. No matter how much the bean counters squeeze, the costs of new gear, innovation, and fixing stuff when it flames out over the weekend blasts many IT budgets into orbit. Yep, even Google’s wizards face this problem.

Net net: Google will have little choice but find a way to monetize clicks, eye balls, customer service, cloud access, storage, and any thing that can be slapped with a price tag. Take that to MBA class.

Cynthia Murrell, July 2, 2024

Smart Software and Non-Essential Jobs Rubble-ized

June 27, 2024

dinosaur30a_thumb_thumbThis essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.

I am not convinced that the end of the world is nigh. I am amused by the accelerationists and the “put on the brakes” crowd. I do find it interesting that some suggest the banking sector will replace one-fifth of its oh so wonderful staff with smart software. Every penny matters when one’s bonus is on the line in carpetland.


Who will be harmed by rolling the AI dice to see who pulls a card from a precarious structure? The people working at AI companies perceive themselves as safe. Others — in jobs that should not exist — are likely to find van life, making TikToks, and cruising less rewarding than making art or working in a bank. Thanks, MSFT good enough like many things these days.

The most interesting comment about the people who will soon be able to find their future elsewhere emerged from that bastion of management excellence OpenAI. The article “OpenAI CTO: AI Could Kill Some Creative Jobs That Maybe Shouldn’t Exist Anyway” presents some startling information allegedly emitted by the Chief Technical Officer of OpenAI. (The same individual who did not know from whence the content processed by OpenAI came.)

The write up reports:

OpenAI’s CTO Mira Murati isn’t worried about such potential negative impacts, suggesting during a talk this month that if AI does kill some creative jobs, those jobs were maybe always a bit replaceable anyway. "I think it’s really going to be a collaborative tool, especially in the creative spaces," [OpenAI’s CTO Ms. Murati allegedly said].

The article explains:

Since OpenAI released ChatGPT to the public, fears that different types of generative AI could take or eliminate jobs have swirled across a range of industries. OpenAI has been pushing its text-to-video Sora tool to Hollywood. Game developers, writers, and voice actors have also expressed anger and frustration over generative AI tools and voices that could take their jobs as companies like Microsoft and Electronic Arts embrace AI.

Several observations:

First, my view is that if a good enough solution replaces a really good but expensive human, smart software will get the job. Money talks.

Second, smart software is percolating through niche and specialized software businesses. Israel plays host to an AI cyber conference. Will policeware and intelware vendors and customers get excited about automating and making smart certain routine business processes. Some of these are just begging to get the old smart software treatment. Some of these systems will have unanticipated job consequences.

Third, each year training of professionals becomes more time consuming, expensive, and difficult. The individuals in the classes want to learn, but in my own lectures I see the impact of less-than-optimal high school, college, and graduate education. When something “new” must be integrated into a process, developers will deliver systems that “just do it.” We’re not talking about putting on sneakers and hitting the gym. We are entering a phase when people don’t know what smart software is doing and don’t have the mental equipment to figure out what’s right and what’s absolutely a waste of time.  Dealing with legal consequences and the need for more skilled humans, smart software is now starting to deliver a fresh set of challenges for keeping professionals up to date and adept.

Net net: Houses of cards can be sensitive to mild perturbations. Then the structure demonstrates structural deficiencies. Watch out below.

Stephen E Arnold, June 27, 2024

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