Good Enough: The New Standard of Excellence
August 20, 2024
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This essay is the work of a dumb dinobaby. No smart software required.
I read an interesting essay about software development. “[The] Biggest Productivity Killers in the Engineering Industry” presents three issues which add to the time and cost of a project. Let’s look at each of these factors and then one trivial downstream consequence of implementing these productivity touchpoints.
The three killers are:
- Working on a project until it meets one’s standards of “perfectionism.” Like “love” and “ethics”, perfectionism is often hard to define without a specific context. A designer might look at an interface and its colors and say, “It’s perfect.” The developer or, heaven forbid, the client looks and says, “That sucks.” Oh, oh.
- Stalling; that is, not jumping right into a project and making progress. I worked at an outfit which valued what it called “an immediate and direct response.” The idea is that action is better than reaction. Plus is demonstrates that one is not fooling around.
- Context switching; that is, dealing with other priorities or interruptions.
I want to highlight one of these “killers” — The need for “good enough.” The essay contains some useful illustrations. Here’s the one for the perfectionism-good enough trade off. The idea is pretty clear. As one chases getting the software or some other task “perfect” means that more time is required. The idea is that if something takes too long, then the value of chasing perfectionism hits a cost wall. Therefore, one should trade off time and value by turning in the work when it is good enough.
The logic is understandable. I do have one concern not addressed in the essay. I believe my concern applies to the other two productivity killers, stalling and interruptions (my term for context switching).
What is this concern?
How about doors falling off aircraft, stranded astronauts, cybersecurity which fails to protect Social Security Numbers, and city governments who cannot determine if compromised data were “good” or “corrupted.” We just know the data were compromised. There are other examples; for instance, the CrowdStrike misstep which affected only a few million people. How did CrowdStrike happen? My hunch is that “good enough” thinking was involved along with someone putting off making sure the internal controls were actually controlling and interruptions so the person responsible for software controls was pulled into a meeting instead of finishing and checking his or her work.
The difficulty is composed of several capabilities; specifically:
- Does the person doing the job know how to make it work in a good enough manner? In my experience, the boss may not and simply wants the fix implemented now or the product shipped immediately.
- Does the company have a culture of excellence or is it similar to big outfits which cannot deliver live streaming content, allow reviewers to write about a product without threatening them, or provide tactics which kill people because no one on the team understands the concept of ethical behavior? Frankly, today I am not sure any commercial enterprise cares about much other than revenue.
- Does anyone in a commercial organization have responsibility to determine the practical costs of shipping a product or delivering a service that does not deliver reliable outputs? Reaction to failed good enough products and services is, in my opinion, the management method applied to downstream problems.
Net net: Good enough, like it or not, is the new gold standard. Or, is that standard like the Olympic medals, an amalgam. The “real” gold is a veneer; the “good” is a coating on enough.
Stephen E Arnold, August 20, 2024
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A Xoogler Reveals Why Silicon Valley Is So Trusted, Loved, and Respected
August 20, 2024
This essay is the work of a dumb dinobaby. No smart software required.
Amazing as it seems, a Xoogler — in this case, the former adult at Google — is spilling the deepest, darkest secrets of success. The slick executive gave a talk at Stanford University. Was the talk a deep fake? I heard that the video was online and then disappeared. Then I spotted a link to a video which purported to be the “real” Ex-Google CEO’s banned interview. It may or may not be at this link because… Google’s policies about censorship are mysterious to me.
Which persona is real: The hard edged executive or the bad actor in the mirror? Thanks, MSFT Copilot. How is the security effort going?
Let’s cut to the chase. I noted the Wall Street Journal’s story “Eric Schmidt Walks Back Claim Google Is Behind on AI Because of Remote Work.” Someone more alert than I noticed an interesting comment; to wit:
If TikTok is banned, here’s what I propose each and every one of you do: Say to your LLM the following: “Make me a copy of TikTok, steal all the users, steal all the music, put my preferences in it, produce this program in the next 30 seconds, release it, and in one hour, if it’s not viral, do something different along the same lines.” That’s the command. Boom, boom, boom, boom. So, in the example that I gave of the TikTok competitor — and by the way, I was not arguing that you should illegally steal everybody’s music — what you would do if you’re a Silicon Valley entrepreneur, which hopefully all of you will be, is if it took off, then you’d hire a whole bunch of lawyers to go clean the mess up, right? But if nobody uses your product, it doesn’t matter that you stole all the content.
And do not quote me.
I want to point out that this snip comes from the Slashdot post from Msmash on August 16, 2024.
Several points dug into my dinobaby brain:
- Granting an interview, letting it be captured to video, and trying to explain away the remarks strikes me as a little wild and frisky. Years ago, this same Googler was allegedly annoyed when an online publication revealed facts about him located via Google.
- Remaining in the news cycle in the midst of a political campaign, a “special operation” in Russia, and the wake of the Department of Justice’s monopoly decision is interesting. Those comments, like the allegedly accurate one quoted above, put the interest in the Google on some people’s radar. Legal eagles are your sensing devices beeping?
- The entitled behavior of saying one thing to students and then mansplaining that the ideas were not reflective of the inner self is an illustration of behavior my mother would have found objectionable. I listened to my mother. To whom does the Xoogler listen?
Net net: Stanford’s president was allegedly making up information and he subsequently resigned. Now a guest lecturer explains that it is okay to act in what some might call an illegal manner. What are those students learning? I would assert that it is not ethical behavior.
Stephen E Arnold, August 20, 2024
Microsoft and Palantir: Moving Up to Higher Impact Levels
August 20, 2024
Microsoft And Palantir Sell AI Spyware To Us Government
While AI is making the news about how it will end jobs, be used for deep fakes, and overturn creativity industries, there’s something that’s not being mentioned: spyware. The Verge writes about how two big technology players are planning to bring spyware to the US government: “Palantir Partners With Microsoft To Sell AI To The Government.”
Palantir and Microsoft recently announced they will combine their software to power services for US defense and intelligence services. Microsoft’s large language models (LLMs) will be used via Azure OpenAI Service with Palantir’s AI Platforms (AIP). These will be used through Microsoft’s classified government cloud environments. This doesn’t explain exactly what the combination of software will do, but there’s speculation.
Palantir is known for its software that analyses people’s personal data and helping governments and organizations with surveillance. Palantir has been very successful when it comes to government contracts:
“Despite its large client list, Palantir didn’t post its first annual profit until 2023. But the AI hype cycle has meant that Palantir’s “commercial business is exploding in a way we don’t know how to handle,” the company’s chief executive officer Alex Carp told Bloomberg in February. The majority of its business is from governments, including that of Israel — though the risk factors section of its annual filing notes that it does not and will not work with “the Chinese communist party.””
Eventually the details about Palantir’s and Microsoft’s partnership will be revealed. It probably won’t be off from what people imagine, but it is guaranteed to be shocking.
Whitney Grace, August 20, 2024
Suddenly: Worrying about Content Preservation
August 19, 2024
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This essay is the work of a dumb dinobaby. No smart software required.
Digital preservation may be becoming a hot topic for those who rarely think about finding today’s information tomorrow or even later today. Two write ups provide some hooks on which thoughts about finding information could be hung.
The young scholar faces some interesting knowledge hurdles. Traditional institutions are not much help. Thanks, MSFT Copilot. Is Outlook still crashing?
The first concerns PDFs. The essay and how to is “Classifying All of the PDFs on the Internet.” A happy quack to the individual who pursued this project, presented findings, and provided links to the data sets. Several items struck me as important in this project research report:
- Tracking down PDF files on the “open” Web is not something that can be done with a general Web search engine. The takeaway for me is that PDFs, like PowerPoint files, are either skipped or not crawled. The author had to resort to other, programmatic methods to find these file types. If an item cannot be “found,” it ceases to exist. How about that for an assertion, archivists?
- The distribution of document “source” across the author’s prediction classes splits out mathematics, engineering, science, and technology. Considering these separate categories as one makes clear that the PDF universe is about 25 percent of the content pool. Since technology is a big deal for innovators and money types, losing or not being able to access these data suggest a knowledge hurdle today and tomorrow in my opinion. An entity capturing these PDFs and making them available might have a knowledge advantage.
- Entities like national libraries and individualized efforts like the Internet Archive are not capturing the full sweep of PDFs based on my experience.
My reading of the essay made me recognize that access to content on the open Web is perceived to be easy and comprehensive. It is not. Your mileage may vary, of course, but this write up illustrates a large, multi-terabyte problem.
The second story about knowledge comes from the Epstein-enthralled institution’s magazine. This article is “The Race to Save Our Online Lives from a Digital Dark Age.” To make the urgency of the issue more compelling and better for the Google crawling and indexing system, this subtitle adds some lemon zest to the dish of doom:
We’re making more data than ever. What can—and should—we save for future generations? And will they be able to understand it?
The write up states:
For many archivists, alarm bells are ringing. Across the world, they are scraping up defunct websites or at-risk data collections to save as much of our digital lives as possible. Others are working on ways to store that data in formats that will last hundreds, perhaps even thousands, of years.
The article notes:
Human knowledge doesn’t always disappear with a dramatic flourish like GeoCities; sometimes it is erased gradually. You don’t know something’s gone until you go back to check it. One example of this is “link rot,” where hyperlinks on the web no longer direct you to the right target, leaving you with broken pages and dead ends. A Pew Research Center study from May 2024 found that 23% of web pages that were around in 2013 are no longer accessible.
Well, the MIT story has a fix:
One way to mitigate this problem is to transfer important data to the latest medium on a regular basis, before the programs required to read it are lost forever. At the Internet Archive and other libraries, the way information is stored is refreshed every few years. But for data that is not being actively looked after, it may be only a few years before the hardware required to access it is no longer available. Think about once ubiquitous storage mediums like Zip drives or CompactFlash.
To recap, one individual made clear that PDF content is a slippery fish. The other write up says the digital content itself across the open Web is a lot of slippery fish.
The fix remains elusive. The hurdles are money, copyright litigation, and technical constraints like storage and indexing resources.
Net net: If you want to preserve an item of information, print it out on some of the fancy Japanese archival paper. An outfit can say it archives, but in reality the information on the shelves is a tiny fraction of what’s “out there”.
Stephen E Arnold, August 19, 2024
Telegram Rolled Over for Russia. Has Google YouTube Become a Circus Animal Too?
August 19, 2024
This essay is the work of a dumb dinobaby. No smart software required.
Most of the people with whom I interact do not know that Telegram apparently took steps to filter content which the Kremlin deemed unsuitable for Russian citizens. Information reaching me in late April 2024 asserted that Ukrainian government units were no longer able to use Telegram Messenger functions to disseminate information to Telegram users in Russia about Mr. Putin’s “special operation.” Telegram has made a big deal about its commitment to free speech, and it has taken a very, very light touch to censoring content and transactions on its basic and “secret” messaging service. Then, at the end of April 2024, Mr. Pavel Durov flipped, apparently in response to either a request or threat from someone in Russia. The change in direction for a messaging app with 900 million users is a peanut compared to Meta WhatsApp five million or so. But when free speech becomes obeisance I take note.
I have been tracking Russian YouTubers because I have found that some of the videos provide useful insights into the impact of the “special operation” on prices, the attitudes of young people, and imagery about the condition of housing, information day-to-day banking matters, and the demeanor of people in the background of some YouTube, TikTok, Rutube, and Kick videos.
I want to mention that Alphabet Google YouTube a couple of years ago took action to suspend Russian state channels from earning advertising revenue from the Google “we pay you” platform. Facebook and the “old” Twitter did this as well. I have heard that Google and YouTube leadership understood that Ukraine wanted those “propaganda channels” blocked. The online advertising giant complied. About 9,000 channels were demonetized or made difficult to find (to be fair, finding certain information on YouTube is not an easy task.) Now Russia has convinced Google to respond to its wishes.
So what? To most people, this is not important. Just block the “bad” content. Get on with life.
I watched a video called “Demonetized! Update and the Future.” The presenter is a former business manager who turned to YouTube to document his view of Russian political, business, and social events. The gentleman — allegedly named “Konstantin” — worked in the US. He returned to Russia and then moved to Uzbekistan. His YouTube channel is (was) titled Inside Russia.
The video “Demonetized! Update and the Future” caught my attention. Please, note, that the video may be unavailable when you read this blog post. “Demonetization” is Google speak for cutting of advertising revenue itself and to the creator.
Several other Russian vloggers producing English language content about Russia, the Land of Putin on the Fritz, have expressed concern about their vlogging since Russia slowed down YouTube bandwidth making some content unwatchable. Others have taken steps to avoid problems; for example, creators Svetlana, Niki, and Nfkrz have left Russia. Others are keeping a low profile.
This raises questions about the management approach in a large and mostly unregulated American high-technology company. According to Inside Russia’s owner Konstantin, YouTube offered no explanation for the demonetization of the channel. Konstantin asserts that YouTube is not providing information to him about its unilateral action. My hunch is that he does not want to come out and say, “The Kremlin pressured an American company to cut off my information about the impact of the ‘special operation’ on Russia.”
Several observations:
- I have heard but not verified that Apple has cooperated with the Kremlin’s wish for certain content to be blocked so that it does not quickly reach Russian citizens. It is unclear what has caused the US companies to knuckle under. My initial thought was, “Money.” These outfits want to obtain revenues from Russia and its federation, hoping to avoid a permanent ban when the “special operation” ends. The inducements (and I am speculating) might also have a kinetic component. That occurs when a person falls out of a third story window and then impacts the ground. Yes, falling out of windows can happen.
- I surmise that the vloggers who are “demonetized” are probably on a list. These individuals and their families are likely to have a tough time getting a Russian government job, a visa, or a passport. The list may have the address for the individual who is generating unacceptable-to-the-Kremlin content. (There is a Google Map for Uzbekistan’s suburb where Konstantin may be living.)
- It is possible that YouTube is doing nothing other than letting its “algorithm” make decisions. Demonetizing Russian YouTubers is nothing more than an unintended consequence of no material significance.
- Does YouTube deserve some attention because its mostly anything-goes approach to content seems to be malleable? For example, I can find information about how to steal a commercial software program owned by a German company via the YouTube search box. Why is this crime not filtered? Is a fellow talking about the “special operation” subject to a different set of rules?
Screen shot of suggested terms for the prompt “Magix Vegas Pro 21 crack” taken on August 16, 2024, at 224 pm US Eastern.
I have seen some interesting corporate actions in my 80 years. But the idea that a country, not particularly friendly to the U.S. at this time, can cause an American company to take what appears to be an specific step designed to curtail information flow is remarkable. Perhaps when Alphabet executives explain to Congress the filtering of certain American news related to events linked to the current presidential campaign more information will be made available?
If Konstantin’s allegations about demonetization are accurate, what’s next on Alphabet, Google, and YouTube’s to-do list for information snuffing or information cleansing?
Stephen E Arnold, August 18, 2024
Good News: Meta To Unleash Automated AI Ads
August 19, 2024
Facebook generated its first revenue streams from advertising. Meta, Facebook’s parent company, continues to make huge profits from ads. Its products use cookies for targeted ads, collect user information to sell, and more. It’s not surprising that AI will soon be entering the picture says Computer Weekly: “Meta’s Zuckerberg Looks Ahead To AI-Generated Adverts.”
Meta increased its second-quarter revenues 22% from its first quarter. The company also reported that the cost of revenue increased by 23% due to higher infrastructure costs and Reality Labs needing a lot of cash. Zuckerberg explained that advertisers used to reach out to his company about the target audiences they wanted to reach. Meta eventually became so advanced that its ad systems predicted target audiences better than the advertisers. Zuckerberg plans for Meta to do the majority of work for advertising agencies. All they will need to provide Meta will be a budget and business objective.
Meta is investing and developing technology to make more money via AI. Meta is playing the long game:
“When asked about the payback time for investments in AI, Meta’s chief financial officer, Susan Li, said: ‘On our core AI work, we continue to take a very return on investment-based approach. We’re still seeing strong returns as improvements to both engagement and ad performance have translated into revenue gains, and it makes sense for us to continue investing here.’
Looking at generative AI (GenAI), she added: “We don’t expect our GenAI products to be a meaningful driver of revenue in 2024, but we do expect that they’re going to open up new revenue opportunities over time that will enable us to generate a solid return off of our investment…’”
Meta might see a slight dip in profit margins because it is investing in better technology, but AI generated ads will pay for themselves, literally.
Whitney Grace, August 19, 2024
An Ed Critique That Pans the Sundar & Prabhakar Comedy Act
August 16, 2024
This essay is the work of a dumb dinobaby. No smart software required.
I read Ed.
Ed refers to Edward Zitron, the thinker behind Where’s Your Ed At. The write up which caught my attention is “Monopoly Money.” I think that Ed’s one-liners will not be incorporated into the Sundar & Prabhakar comedy act. The flubbed live demos are knee slappers, but Ed’s write up is nipping at the heels of the latest Googley gaffe.
Young people are keen observers of certain high-technology companies. What happens if one of the giants becomes virtual and moves to a Dubai-type location? Who has jurisdiction? Regulatory enforcement delayed means big high-tech outfits are more portable than old-fashioned monopolies. Thanks, MSFT Copilot. Big industrial images are clearly a core competency you have.
Ed’s focus is on the legal decision which concluded that the online advertising company is a monopoly in “general text advertising.” The essay states:
The ruling precisely explains how Google managed to limit competition and choice in the search and ad markets. Documents obtained through discovery revealed the eye-watering amounts Google paid to Samsung ($8 billion over four years) and Apple ($20 billion in 2022 alone) to remain the default search engine on their devices, as well as Mozilla (around $500 million a year), which (despite being an organization that I genuinely admire, and that does a lot of cool stuff technologically) is largely dependent on Google’s cash to remain afloat.
Ed notes:
Monopolies are a big part of why everything feels like it stopped working.
Ed is on to something. The large technology outfits in the US control online. But one of the downstream consequences of what I call the Silicon Valley way or the Googley approach to business is that other industries and market sectors have watched how modern monopolies work. The result is that concentration of power has not been a regulatory priority. The role of data aggregation has been ignored. As a result, outfits like Kroger (a grocery company) is trying to apply Googley tactics to vegetables.
Ed points out:
Remember when “inflation” raised prices everywhere? It’s because the increasingly-dwindling amount of competition in many consumer goods companies allowed them to all raise their prices, gouging consumers in a way that should have had someone sent to jail rather than make $19 million for bleeding Americans dry. It’s also much, much easier for a tech company to establish one, because they often do so nestled in their own platforms, making them a little harder to pull apart. One can easily say “if you own all the grocery stores in an area that means you can control prices of groceries,” but it’s a little harder to point at the problem with the tech industry, because said monopolies are new, and different, yet mostly come down to owning, on some level, both the customer and those selling to the customer.
Blue chip consulting firms flip this comment around. The points Ed makes are the recommendations and tactics the would-be monopolists convert to action plans. My reaction is, “Thanks, Silicon Valley. Nice contribution to society.”
Ed then gets to artificial intelligence, definitely a hot topic. He notes:
Monopolies are inherently anti-consumer and anti-innovation, and the big push toward generative AI is a blatant attempt to create another monopoly — the dominance of Large Language Models owned by Microsoft, Amazon, Google and Meta. While this might seem like a competitive marketplace, because these models all require incredibly large amounts of cloud compute and cash to both train and maintain, most companies can’t really compete at scale.
Bingo.
I noted this Ed comment about AI too:
This is the ideal situation for a monopolist — you pay them money for a service and it runs without you knowing how it does so, which in turn means that you have no way of building your own version. This master plan only falls apart when the “thing” that needs to be trained using hardware that they monopolize doesn’t actually provide the business returns that they need to justify its existence.
Ed then makes a comment which will cause some stakeholders to take a breath:
As I’ve written before, big tech has run out of hyper-growth markets to sell into, leaving them with further iterations of whatever products they’re selling you today, which is a huge problem when big tech is only really built to rest on its laurels. Apple, Microsoft and Amazon have at least been smart enough to not totally destroy their own products, but Meta and Google have done the opposite, using every opportunity to squeeze as much revenue out of every corner, making escape difficult for the customer and impossible for those selling to them. And without something new — and no, generative AI is not the answer — they really don’t have a way to keep growing, and in the case of Meta and Google, may not have a way to sustain their companies past the next decade. These companies are not built to compete because they don’t have to, and if they’re ever faced with a force that requires them to do good stuff that people like or win a customer’s love, I’m not sure they even know what that looks like.
Viewed from a Googley point of view, these high-technology outfits are doing what is logical. That’s why the Google advertisement for itself troubled people. The person writing his child willfully used smart software. The fellow embodied a logical solution to the knotty problem of feelings and appropriate behavior.
Ed suggests several remedies for the Google issue. These make sense, but the next step for Google will be an appeal. Appeals take time. US government officials change. The appetite to fight legions of well resourced lawyers can wane. The decision reveals some interesting insights into the behavior of Google. The problem now is how to alter that behavior without causing significant market disruption. Google is really big, and changes can have difficult-to-predict consequences.
The essay concludes:
I personally cannot leave Google Docs or Gmail without a significant upheaval to my workflow — is a way that they reinforce their monopolies. So start deleting sh*t. Do it now. Think deeply about what it is you really need — be it the accounts you have and the services you need — and take action. They’re not scared of you, and they should be.
Interesting stance.
Several observations:
- Appeals take time. Time favors outfits like losers of anti-trust cases.
- Google can adapt and morph. The size and scale equip the Google in ways not fathomable to those outside Google.
- Google is not Standard Oil. Google is like AT&T. That break up resulted in reconsolidation and two big Baby Bells and one outside player. So a shattered Google may just reassemble itself. The fancy word for this is emergent.
Ed hits some good points. My view is that the Google fumbles forward putting the Sundar & Prabhakar Comedy Act in every city the digital wagon can reach.
Stephen E Arnold, August 16, 2024
A Familiar Cycle: The Frustration of Almost Solving the Search Problem
August 16, 2024
This essay is the work of a dumb dinobaby. No smart software required.
Search and retrieval is a difficult problem. The solutions have ranged from scrolls with labels to punched cards and rods to bags of words. Each innovation or advance sparked new ideas. Boolean gave way to natural language. Natural language evolved into semi-smart systems. Now we are in the era of what seems to be smart software. Like the punch card systems, users became aware of the value of consistent, accurate indexing. Today one expects a system to “know” what the user wants. Instead of knowing index terms, one learns to be a prompt engineer.
Search and retrieval is not “solved” using large language models. LLMs are a step forward on a long and difficult path. The potential financial cost of thinking that the methods are a sure-fire money machine is high. Thanks, MSFT Copilot. How was DEFCON?
I read “LLM Progress Is Slowing — What Will It Mean for AI?.” The write up makes clear that some of the excitement of smart software which can makes sense of natural language queries (prompts) has lost some of its shine. This type of insight is one that probably existed when a Babylonian tablet maker groused about not having an easy way to stack up clay tablets for the money guy. Search and retrieval is essential for productive work. A system which makes that process less of a hassle is welcomed. After a period of time one learns that the approach is not quite where the user wants it to be. Researchers and innovators hear the complaint and turn their attention to improving search and retrieval … again.
The write up states:
The leap from GPT-3 to GPT-3.5 was huge, propelling OpenAI into the public consciousness. The jump up to GPT-4 was also impressive, a giant step forward in power and capacity. Then came GPT-4 Turbo, which added some speed, then GPT-4 Vision, which really just unlocked GPT-4’s existing image recognition capabilities. And just a few weeks back, we saw the release of GPT-4o, which offered enhanced multi-modality but relatively little in terms of additional power. Other LLMs, like Claude 3 from Anthropic and Gemini Ultra from Google, have followed a similar trend and now seem to be converging around similar speed and power benchmarks to GPT-4. We aren’t yet in plateau territory — but do seem to be entering into a slowdown. The pattern that is emerging: Less progress in power and range with each generation.
This is an echo of the complaints I heard about Dr. Salton’s SMART search system.
The “fix” according to the write up may be to follow one of these remediation paths:
- More specialization
- New user interfaces
- Open source large language models
- More and better data
- New large language model architectures.
These are ideas bolted to the large language model approach to search and retrieval. I think each has upsides and downsides. These deserve thoughtful discussion. However, the evolution of search-and-retrieval has been an evolutionary process. Those chaos and order thinkers at the Santa Fe Institute suggest that certain “things” self organize and emerge. The idea has relevance to what happens with each “new” approach to search and retrieval.
The cited write up concludes with this statement:
One possible pattern that could emerge for LLMs: That they increasingly compete at the feature and ease-of-use levels. Over time, we could see some level of commoditization set in, similar to what we’ve seen elsewhere in the technology world. Think of, say, databases and cloud service providers. While there are substantial differences between the various options in the market, and some developers will have clear preferences, most would consider them broadly interchangeable. There is no clear and absolute “winner” in terms of which is the most powerful and capable.
I think the idea about competition is mostly correct. However, what my impression of search and retrieval as a technology thread is that progress is being made. I find it encouraging that more users are interacting with systems. Unfortunately search and retrieval is not solved by generating a paragraph a high school student can turn into a history teacher as an original report.
Effective search and retrieval is not just a prompt box. Effective information access remains a blend of extraordinarily trivial activities. For instance, a conversation may suggest a new way to locate relevant information. Reading an article or a longer document may trigger an unanticipated connection between ant colonies and another task-related process. The act of looking at different sources may lead to a fact previously unknown which leads in turn to another knowledge insight. Software alone cannot replicate these mental triggers.
LLMs like stacked clay tablets provide challenges and utility. However, search and retrieval remains a work in progress. LLMs, like semantic ad matching, or using one’s search history as a context clue, are helpful. But opportunities for innovation exist. My view is that the grousing about LLM limitations is little more than a recognition that converting a human concept or information need to an “answer” is a work in progress. The difference is that today billions of dollars have been pumped into smart software in the hope that information retrieval is solved.
Sorry, it is not. Therefore, the stakes of realizing that the golden goose may not lay enough eggs to pay off the cost of the goose itself. Twenty years ago search and retrieval was not a sector consuming billions of dollars in the span of a couple of years. That’s what is making people nervous about LLMs. Watching Delphi or Entopia fail was expensive, but the scale of the financial loss and the emotional cost of LLM failure is a different kettle of fish.
Oh, and those five “fixes” in the bullet points from the write up. None will solve the problem of search and retrieval.
Stephen E Arnold, August 16, 2024
Deep Fake Service?
August 16, 2024
This essay is the work of a dumb dinobaby. No smart software required.
What sets DeepLive apart is that one needs only a single image and the video of the person whose face you want to replace. The technology — assuming it is functioning as marketed — makes it clear that swapping faces on videos can be done. Will the technology derail often-controversial facial recognition systems?
The Web site provides testimonials and some examples of DeepLive in action.
The company says:
Deep Live Cam is an open-source tool for real-time face swapping and one-click video deepfakes. It can replace faces in videos or images using a single photo, ideal for video production, animation, and various creative projects.
The software is available as open source. The developers says that it includes “ethical safeguards.” But just in case these don’t work, DeepLive posts this message on its Web site:
Built-in checks prevent processing of inappropriate content, ensuring legal and ethical use.
The software has a couple of drawbacks:
- It is not clear if this particular code base is on an open source repository. There are a number of Deep Live this and thats.
- There is no active Web page link to the “Get Started” button
- There is minimal information about the “owner” of the software.
Other than that DeepLive is a good example of a deep fake. (An interesting discussion appears in HackerNews and Ars Technica.) If the system is stable and speedy, AI-enabled tools to create content objects for a purpose has taken a step forward. Bad actors are probably going to take note and give the system a spin.
Stephen E Arnold, August 16, 2024
Pragmatic AI: Individualized Monitoring
August 15, 2024
This essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.
In June 2024 at the TechnoSecurity & Digital Forensics conference, one of the cyber investigators asked me, “What are some practical uses of AI in law enforcement?” I told the person that I would send him a summary of my earlier lecture called “AI for LE.” He said, “Thanks, but what should I watch to see some AI in action.” I told him to pay attention to the Kroger pricing methods. I had heard that Kroger was experimenting with altering prices based on certain signals. The example I gave is that if the Kroger is located in a certain zip code, then the Kroger stores in that specific area would use dynamic pricing. The example I gave was similar to Coca-Cola’s tests of a vending machine that charged more if the temperature was hot. In the Kroger example, a hot day would trigger a change in the price of a frozen dessert. He replied, “Kroger?” I said, “Yes, Kroger is experimenting with AI in order to detect specific behaviors and modify prices to reflect those signals.” What Kroger is doing will be coming to law enforcement and intelligence operations. Smart software monitors the behavior of a prisoner, for example, and automatically notifies an investigator when a certain signal is received. I recall mentioning that smart software, signals, and behavior change or direct action will become key components of a cyber investigator’s tool kit. He said, laughing, “Kroger. Interesting.”
Thanks, MSFT Copilot. Good enough.
I learned that Kroger’s surveillance concept is now not a rumor discussed at a neighborhood get together. “‘Corporate Greed Is Out of Control’: Warren Slams Kroger’s AI Pricing Scheme” reveals that elected officials and probably some consumer protection officials may be aware of the company’s plans for smart software. The write up reports:
Warren (D-Mass.) was joined by Sen. Bob Casey (D-Pa.) on Wednesday in writing a letter to the chairman and CEO of the Kroger Company, Rodney McMullen, raising concerns about how the company’s collaboration with AI company IntelligenceNode could result in both privacy violations and worsened inequality as customers are forced to pay more based on personal data Kroger gathers about them “to determine how much price hiking [they] can tolerate.” As the senators wrote, the chain first introduced dynamic pricing in 2018 and expanded to 500 of its nearly 3,000 stores last year. The company has partnered with Microsoft to develop an Electronic Shelving Label (ESL) system known as Enhanced Display for Grocery Environment (EDGE), using a digital tag to display prices in stores so that employees can change prices throughout the day with the click of a button.
My view is that AI orchestration will allow additional features and functions. Some of these may be appropriate for use in policeware and intelware systems. Kroger makes an effort to get individuals to sign up for a discount card. Also, Kroger wants users to install the Kroger app. The idea is that discounts or other incentives may be “awarded” to the customer who takes advantages of the services.
However, I am speculating that AI orchestration will allow Kroger to implement a chain of actions like this:
- Customer with a mobile phone enters the store
- The store “acknowledges” the customer
- The customer’s spending profile is accessed
- The customer is “known” to purchase upscale branded ice cream
- The price for that item automatically changes as the customer approaches the display
- The system records the item bar code and the customer ID number
- At check out, the customer is charged the higher price.
Is this type of AI orchestration possible? Yes. Is it practical for a grocery store to deploy? Yes because Kroger uses third parties to provide its systems and technical capabilities for many applications.
How does this apply to law enforcement? Kroger’s use of individualized tracking may provide some ideas for cyber investigators.
As large firms with the resources to deploy state-of-the-art technology to boost sales, know the customer, and adjust prices at the individual shopper level, the benefit of smart software become increasingly visible. Some specialized software systems lag behind commercial systems. Among the reasons are budget constraints and the often complicated procurement processes.
But what is at the grocery store is going to become a standard function in many specialized software systems. These will range from security monitoring systems which can follow a person of interest in an specific area to automatically updating a person of interest’s location on a geographic information module.
If you are interested in watching smart software and individualized “smart” actions, just pay attention at Kroger or a similar retail outfit.
Stephen E Arnold, August 15, 2024
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