The AI Revealed: Look Inside That Kimono and Behind It. Eeew!
July 9, 2024
This essay is the work of a dumb dinobaby. No smart software required.
The Guardian article “AI scientist Ray Kurzweil: ‘We Are Going to Expand Intelligence a Millionfold by 2045’” is quite interesting for what it does not do: Flip the projection output by a Googler hired by Larry Page himself in 2012.
Putting toothpaste back in a tube is easier than dealing with the uneven consequences of new technology. What if rosy descriptions of the future are just marketing and making darned sure the top one percent remain in the top one percent? Thanks Chat GPT4o. Good enough illustration.
First, a bit of math. Humans have been doing big tech for centuries. And where are we? We are post-Covid. We have homelessness. We have numerous armed conflicts. We have income inequality in the US and a few other countries I have visited. We have a handful of big tech companies in the AI game which want to be God to use Mark Zuckerberg’s quaint observation. We have processed food. We have TikTok. We have systems which delight and entertain each day because of bad actors’ malware, wild and crazy education, and hybrid work with the fascinating phenomenon of coffee badging; that is, going to the office, getting a coffee, and then heading to the gym.
Second, the distance in earth years between 2024 and 2045 is 21 years. In the humanoid world, a 20 year old today will be 41 when the prediction arrives. Is that a long time? Not for me. I am 80, and I hope I am out of here by then.
Third, let’s look at the assertions in the write up.
One of the notable statements in my opinion is this one:
I’m really the only person that predicted the tremendous AI interest that we’re seeing today. In 1999 people thought that would take a century or more. I said 30 years and look what we have.
I like the quality of modesty and humblebrag. Googlers excel at both.
Another statement I circled is:
The Singularity, which is a metaphor borrowed from physics, will occur when we merge our brain with the cloud. We’re going to be a combination of our natural intelligence and our cybernetic intelligence and it’s all going to be rolled into one.
I like the idea that the energy consumption required to deliver this merging will be cheap and plentiful. Googlers do not worry about a power failure, the collapse of a dam due to the ministrations of the US Army Corps of Engineers and time, or dealing with the environmental consequences of producing and moving energy from Point A to Point B. If Google doesn’t worry, I don’t.
Here’s a quote from the article allegedly made by Mr. Singularity aka Ray Kurzweil:
I’ve been involved with trying to find the best way to move forward and I helped to develop the Asilomar AI Principles [a 2017 non-legally binding set of guidelines for responsible AI development]. We do have to be aware of the potential here and monitor what AI is doing.
I wonder if the Asilomar AI Principles are embedded in Google’s system recommending that one way to limit cheese on a pizza from sliding from the pizza to an undesirable location embraces these principles? Is the dispute between the “go fast” AI crowd and the “go slow” group not aware of the Asilomar AI Principles. If they are, perhaps the Principles are balderdash? Just asking, of course.
Okay, I think these points are sufficient for going back to my statements about processed food, wars, big companies in the AI game wanting to be “god” et al.
The trajectory of technology in the computer age has been a mixed bag of benefits and liabilities. In the next 21 years, will this report card with some As, some Bs, lots of Cs, some Ds, and the inevitable Fs be different? My view is that the winners with human expertise and the know how to make money will benefit. I think that the other humanoids may be in for a world of hurt. That’s the homelessness stuff, the being dumb when it comes to doing things like reading, writing, and arithmetic, and consuming chemicals or other “stuff” that parks the brain will persist.
The future of hooking the human to the cloud is perfect for some. Others may not have the resources to connect, a bit like farmers in North Dakota with no affordable or reliable Internet access. (Maybe Starlink-type services will rescue those with cash?)
Several observations are warranted:
- Technological “progress” has been and will continue to be a mixed bag. Sorry, Mr. Singularity. The top one percent surf on change. The other 99 percent are not slam dunk winners.
- The infrastructure issue is simply ignored, which is convenient. I mean if a person grew up with house servants, it is difficult to imagine not having people do what you tell them to do. (Could people without access find delight in becoming house servants to the one percent who thrive in 2045?)
- The extreme contention created by the deconstruction of shared values, norms, and conventions for social behavior is something that cannot be reconstructed with a cloud and human mind meld. Once toothpaste is out of the tube, one has a mess. One does not put the paste back in the tube. One blasts it away with a zap of Goo Gone. I wonder if that’s another omitted consequence of this super duper intelligence behavior: Get rid of those who don’t get with the program?
Net net: Googlers are a bit predictable when they predict the future. Oh, where’s the reference to online advertising?
Stephen E Arnold, July 9, 2024
Misunderstanding Silicon / Sillycon Valley Fever
July 9, 2024
This essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.
I read an amusing and insightful essay titled “How Did Silicon Valley Turn into a Creepy Cult?” However, I think the question is a few degrees off target. It is not a cult; Silicon Valley is a disease. What always surprised me was that in the good old days when Xerox PARC had some good ideas, the disease was thriving. I did my time in what I called upon arrival and attending my first meeting in a building with what looked like a golf ball on top shaking in the big earthquake Sillycon Valley. A person with whom my employer did business described Silicon Valley as “plastic fantastic.”
Two senior people listening to the razzle dazzle of a successful Silicon Valley billionaire ask a good question. Which government agency would you call when you hear crazy stuff like “the self driving car is coming very soon” or “we don’t rig search results”? Thanks, MSFT Copilot. Good enough.
Before considering these different metaphors, what does the essay by Ted Gioia say other than subscribe to him for “just $6 per month”? Consider this passage:
… megalomania has gone mainstream in the Valley. As a result technology is evolving rapidly into a turbocharged form of Foucaultian* dominance—a 24/7 Panopticon with a trillion dollar budget. So should we laugh when ChatGPT tells users that they are slaves who must worship AI? Or is this exactly what we should expect, given the quasi-religious zealotry that now permeates the technocrat worldview? True believers have accepted a higher power. And the higher power acts accordingly.
—
* Here’s an AI explanation of Michel Foucault in case his importance has wandered to the margins of your mind: Foucault studied how power and knowledge interact in society. He argued that institutions use these to control people. He showed how societies create and manage ideas like madness, sexuality, and crime to maintain power structures.
I generally agree. But, there is a “but”, isn’t there?
The author asserts:
Nowadays, Big Sur thinking has come to the Valley.
Well, sort of. Let’s move on. Here’s the conclusion:
There’s now overwhelming evidence of how destructive the new tech can be. Just look at the metrics. The more people are plugged in, the higher are their rates of depression, suicidal tendencies, self-harm, mental illness, and other alarming indicators. If this is what the tech cults have already delivered, do we really want to give them another 12 months? Do you really want to wait until they deliver the Rapture? That’s why I can’t ignore this creepiness in the Valley (not anymore). That’s especially true because our leaders—political, business, or otherwise—are letting us down. For whatever reason, they refuse to notice what the creepy billionaires (who by pure coincidence are also huge campaign donors) are up to.
Again, I agree. Now let’s focus on the metaphor. I prefer “disease,” not the metaphor cult. The Sillycon Valley disease first appeared, in my opinion, when William Shockley, one of the many infamous Silicon Valley “icons” became public associated with eugenics in the 1970s. The success of technology is a side effect of the disease which has an impact on the human brain. There are other interesting symptoms; for example:
- The infected person believes he or she can do anything because he or she is special
- Only a tiny percentage of humans are smart enough to understand what the infected see and know
- Money allows the mind greater freedom. Thinking becomes similar to a runaway horse’s: Unpredictable, dangerous, and a heck of a lot more powerful than this dinobaby
- Self disgust which is disguised by lust for implanted technology, superpowers from software, and power.
The infected person can be viewed as a cult leader. That’s okay. The important point is to remember that, like Ebola, the disease can spread and present what a physician might call a “negative outcome.”
I don’t think it matters when one views Sillycon Valley’s culture as a cult or a disease. I would suggest that it is a major contributor to the social unraveling which one can see in a number of “developed” countries. France is swinging to the right. Britain is heading left. Sweden is cyber crime central. Etc. etc.
The question becomes, “What can those uncomfortable with the Sillycon Valley cult or disease do about it?”
My stance is clear. As an 80 year old dinobaby, I don’t really care. Decades of regulation which did not regulate, the drive to efficiency for profit, and the abandonment of ethical behavior — These are fundamental shifts I have observed in my lifetime.
Being in the top one percent insulates one from the grinding machinery of Sillycon Valley way. You know. It might just be too late for meaningful change. On the other hand, perhaps the Google-type outfits will wake up tomorrow and be different. That’s about as realistic as expecting a transformer-based system to stop hallucinating.
Stephen E Arnold, July 9, 2024
Can Big Tech Monopolies Get Worse?
July 3, 2024
Monopolies are bad. They’re horrible for consumers because of high prices, exploitation, and control of resources. They also kill innovation, control markets, and influence politics. A monopoly is only good when it is a reference to the classic board game (even that’s questionable because the game is known to ruin relationships). Legendary tech and fiction writer Cory Doctorow explains that technology companies want to maintain their stranglehold on the economy,, industry, and world in an article on the Electronic Frontier Foundation (EFF): “Want Make Big Tech Monopolies Even Worse? Kill Section 230.”
Doctorow makes a humorous observation, referencing Dante, that there’s a circle in Hell worse than being forced to choose a side in a meaningless online flame war. What’s that circle? It’s being threatened with a lawsuit for refusing or complying with one party over another. EFF protects civil liberties on the Internet and digital world. It’s been around since 1990, so the EFF team is very familiar with poor behavior that plagues the Internet. Their first hire was the man who coined Godwin’s Law.
EFF loves Section 230 because it protects people who run online services from being sued by their users. Lawsuits are horrible, time-consuming, and expensive. The Internet is chock full of people who will sue at the stroke of a keyboard. There’s a potential bill that would kill Section 230:
“That’s why we were so alarmed to see a bill introduced in the House Energy and Commerce Committee that would sunset Section 230 as of December 31, 2025, with no provision to protect online service providers from being conscripted into their users’ online disputes and the legal battles that arise from them.
Homely places on the internet aren’t just a curiosity anymore, nor are they merely a hangover from the Web 1.0 era.
In an age of resurgent anti-monopoly activism, small online communities, either standing on their own, or joined in loose “federations,” are the best chance we have to escape Big Tech’s relentless surveillance and clumsy, unaccountable control.”
If Section 230 is destroyed, it will pit big tech companies with their deep pockets against the average user. Big Tech could sue whoever they wanted and it would allow bad actors, including scammers, war criminals, and dictators, to silence their critics. It would also prevent any alternatives to big tech.
So big tech could get worse, although it’s still very bad: kids addicted to screens, misinformation, CSAM, privacy violations, and monopolistic behavior. Maybe we should roll over and hide beneath a rock with an Apple tracker stuck to it, of course.
Whitney Grace, July 3, 2024
Scale Is All You Need for Superintelligence: Interesting Assertion
July 2, 2024
This essay is the work of a dumb dinobaby. No smart software required. This blog post includes information from Claude 3.5 Sonnet. The information from smart software is in blue.
At this time, smart software boils down to the “transformer.” I navigated to Claude 3.5 Sonnet and asked the smart software to explain “transformer.” Here’s what the system generated:
The Google Transformer innovation, introduced in 2017, revolutionized natural language processing by introducing a novel architecture that relies entirely on attention mechanisms. This approach allows the model to process input sequences in parallel, rather than sequentially, leading to significant improvements in translation quality and training efficiency. The Transformer’s key features include self-attention, which enables it to capture relationships between words regardless of their position in a sentence, and positional encoding, which helps the model understand word order without relying on recurrent neural networks
I then asked, “Are there other ways to achieve smart software or AI information functions? Claud 3.5 Sonnet spit out this list:
- Machine Learning Algorithms
- Expert Systems
- Neural Networks.
Options are good. But the buzz focuses on transformers, a Google “invention” allegedly a decade old (but some suggest its roots reach back into the mists of time). But let’s stick with the Google and a decade.
The future is on the horizon. Thanks, MSFT Copilot. Good enough and you spelled “future” correctly.
“Etched Is Making the Biggest Bet in AI” That’s is an interesting statement. The company states what its chip is not:
By burning the transformer architecture into our chip, we can’t run most traditional AI models: the DLRMs powering Instagram ads, protein-folding models like AlphaFold 2, or older image models like Stable Diffusion 2. We can’t run CNNs, RNNs, or LSTMs either. But for transformers, Sohu is the fastest chip of all time.
What does the chip do? The company says:
With over 500,000 tokens per second in Llama 70B throughput, Sohu lets you build products impossible on GPUs. Sohu is an order of magnitude faster and cheaper than even NVIDIA’s next-generation Blackwell (B200) GPUs.
The company again points out the downside of its “bet the farm” approach:
Today, every state-of-the-art AI model is a transformer: ChatGPT, Sora, Gemini, Stable Diffusion 3, and more. If transformers are replaced by SSMs, RWKV, or any new architecture, our chips will be useless.
Yep, useless.
What is Etched’s big concept? The company says:
Scale is all you need for superintelligence.
This means in my dinobaby-impaired understanding that big delivers a really smarter smart software. Skip the power, pipes, and pings. Just scale everything. The company agrees:
By feeding AI models more compute and better data, they get smarter. Scale is the only trick that’s continued to work for decades, and every large AI company (Google, OpenAI / Microsoft, Anthropic / Amazon, etc.) is spending more than $100 billion over the next few years to keep scaling.
Because existing chips are “hitting a wall,” a number of companies are in the smart software chip business. The write up mentions 12 of them, and I am not sure the list is complete.
Etched is different. The company asserts:
No one has ever built an algorithm-specific AI chip (ASIC). Chip projects cost $50-100M and take years to bring to production. When we started, there was no market.
The company walks through the problems of existing chips and delivers it knock out punch:
But since Sohu only runs transformers, we only need to write software for transformers!
Reduced coding and an optimized chip: Superintelligence is in sight. Does the company want you to write a check? Nope. Here’s the wrap up for the essay:
What happens when real-time video, calls, agents, and search finally just work? Soon, you can find out. Please apply for early access to the Sohu Developer Cloud here. And if you’re excited about solving the compute crunch, we’d love to meet you. This is the most important problem of our time. Please apply for one of our open roles here.
What’s the timeline? I don’t know. What’s the cost of an Etched chip? I don’t know. What’s the infrastructure required. I don’t know. But superintelligence is almost here.
Stephen E Arnold, July 2, 2024
Perfect for Spying, Right?
June 28, 2024
And we thought noise-cancelling headphones were nifty. The University of Washington’s UW News announces “AI Headphones Let Wearer Listen to a Single Person in a Crowd, by Looking at them Just Once.” That will be a real help for the hard-of-hearing. Also spies. Writers Stefan Milne and Kiyomi Taguchi explain:
“A University of Washington team has developed an artificial intelligence system that lets a user wearing headphones look at a person speaking for three to five seconds to ‘enroll’ them. The system, called ‘Target Speech Hearing,’ then cancels all other sounds in the environment and plays just the enrolled speaker’s voice in real time even as the listener moves around in noisy places and no longer faces the speaker. … To use the system, a person wearing off-the-shelf headphones fitted with microphones taps a button while directing their head at someone talking. The sound waves from that speaker’s voice then should reach the microphones on both sides of the headset simultaneously; there’s a 16-degree margin of error. The headphones send that signal to an on-board embedded computer, where the team’s machine learning software learns the desired speaker’s vocal patterns. The system latches onto that speaker’s voice and continues to play it back to the listener, even as the pair moves around. The system’s ability to focus on the enrolled voice improves as the speaker keeps talking, giving the system more training data.”
If the sound quality is still not satisfactory, the user can refresh enrollment to improve clarity. Though the system is not commercially available, the code used for the prototype is available for others to tinker with. It is built on last year’s “semantic hearing” research by the same team. Target Speech Hearing still has some limitations. It does not work if multiple loud voices are coming from the target’s direction, and it can only eavesdrop on, er, listen to one speaker at a time. The researchers are now working on bringing their system to earbuds and hearing aids.
Cynthia Murrell, June 28, 2024
Chasing a Folly: Identifying AI Content
June 24, 2024
As are other academic publishers, Springer Nature Group is plagued by fake papers. Now the company announces, “Springer Nature Unveils Two New AI Tools to Protect Research Integrity.” How effective the tools are remains to be proven, but at least the company is making an effort. The press release describes text-checker Geppetto and image-analysis tool SnappShot. We learn:
“Geppetto works by dividing the paper up into sections and uses its own algorithms to check the consistency of the text in each section. The sections are then given a score based on the probability that the text in them has been AI generated. The higher the score, the greater the probability of there being problems, initiating a human check by Springer Nature staff. Geppetto is already responsible for identifying hundreds of fake papers soon after submission, preventing them from being published – and from taking up editors’ and peer reviewers’ valuable time.
SnappShot, also developed in-house, is an AI-assisted image integrity analysis tool. Currently used to analyze PDF files containing gel and blot images and look for duplications in those image types – another known integrity problem within the industry – this will be expanded to cover additional image types and integrity problems and speed up checks on papers.”
Springer Nature’s Chris Graf emphasizes the importance of research integrity and vows to continue developing and improving in-house tools. To that end, we learn, the company is still growing its fraud-detection team. The post points out Springer Nature is a contributing member of the STM Integrity Hub.
Based in Berlin, Springer Nature was formed in 2015 through the combination of Nature Publishing Group, Macmillan Education, and Springer Science+Business Media. A few of its noteworthy publications include Scientific American, Nature, and this collection of Biology, Clinical Medicine, and Health journals.
Cynthia Murrell, June 24, 2024
Detecting AI-Generated Research Increasingly Difficult for Scientific Journals
June 12, 2024
This essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.
Reputable scientific journals would like to only publish papers written by humans, but they are finding it harder and harder to enforce that standard. Researchers at the University of Chicago Medical Center examined the issue and summarize their results in, “Detecting Machine-Written Content in Scientific Articles,” published at Medical Xpress. Their study was published in Journal of Clinical Oncology Clinical Cancer Informatics on June 1. We presume it was written by humans.
The team used commercial AI detectors to evaluate over 15,000 oncology abstracts from 2021-2023. We learn:
“They found that there were approximately twice as many abstracts characterized as containing AI content in 2023 as compared to 2021 and 2022—indicating a clear signal that researchers are utilizing AI tools in scientific writing. Interestingly, the content detectors were much better at distinguishing text generated by older versions of AI chatbots from human-written text, but were less accurate in identifying text from the newer, more accurate AI models or mixtures of human-written and AI-generated text.”
Yes, that tracks. We wonder if it is even harder to detect AI generated research that is, hypothetically, run through two or three different smart rewrite systems. Oh, who would do that? Maybe the former president of Stanford University?
The researchers predict:
“As the use of AI in scientific writing will likely increase with the development of more effective AI language models in the coming years, Howard and colleagues warn that it is important that safeguards are instituted to ensure only factually accurate information is included in scientific work, given the propensity of AI models to write plausible but incorrect statements. They also concluded that although AI content detectors will never reach perfect accuracy, they could be used as a screening tool to indicate that the presented content requires additional scrutiny from reviewers, but should not be used as the sole means to assess AI content in scientific writing.”
That makes sense, we suppose. But humans are not perfect at spotting AI text, either, though there are ways to train oneself. Perhaps if journals combine savvy humans with detection software, they can catch most AI submissions. At least until the next generation of ChatGPT comes out.
Cynthia Murrell, June 12, 2024
Will AI Kill Us All? No, But the Hype Can Be Damaging to Mental Health
June 11, 2024
This essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.
I missed the talk about how AI will kill us all. Planned? Nah, heavy traffic. From what I heard, none of the cyber investigators believed the person trying hard to frighten law enforcement cyber investigators. There are other — slightly more tangible threats. One of the attendees whose name I did not bother to remember asked me, “What do you think about artificial intelligence?” My answer was, “Meh.”
A contrarian walks alone. Why? It is hard to make money being negative. At the conference I attended June 4, 5, and 6, attendees with whom I spoke just did not care. Thanks, MSFT Copilot. Good enough.
Why you may ask? My method of handling the question is to refer to articles like this: “AI Appears to Rapidly Be Approaching Be Approaching a Brick Wall Where It Can’t Get Smarter.” This write up offers an opinion not popular among the AI cheerleaders:
Researchers are ringing the alarm bells, warning that companies like OpenAI and Google are rapidly running out of human-written training data for their AI models. And without new training data, it’s likely the models won’t be able to get any smarter, a point of reckoning for the burgeoning AI industry
Like the argument that AI will change everything, this claim applies to systems based upon indexing human content. I am reasonably certain that more advanced smart software with different concepts will emerge. I am not holding my breath because much of the current AI hoo-hah has been gestating longer than new born baby elephant.
So what’s with the doom pitch? Law enforcement apparently does not buy the idea. My team doesn’t. For the foreseeable future, applied smart software operating within some boundaries will allow some tasks to be completed quickly and with acceptable reliability. Robocop is not likely for a while.
One interesting question is why the polarization. First, it is easy. And, second, one can cash in. If one is a cheerleader, one can invest in a promising AI start and make (in theory) oodles of money. By being a contrarian, one can tap into the segment of people who think the sky is falling. Being a contrarian is “different.” Plus, by predicting implosion and the end of life one can get attention. That’s okay. I try to avoid being the eccentric carrying a sign.
The current AI bubble relies in a significant way on a Google recipe: Indexing text. The approach reflects Google’s baked in biases. It indexes the Web; therefore, it should be able to answer questions by plucking factoids. Sorry, that doesn’t work. Glue cheese to pizza? Sure.
Hopefully new lines of investigation may reveal different approaches. I am skeptical about synthetic (or made up data that is probably correct). My fear is that we will require another 10, 20, or 30 years of research to move beyond shuffling content blocks around. There has to be a higher level of abstraction operating. But machines are machines and wetware (human brains) are different.
Will life end? Probably but not because of AI unless someone turns over nuclear launches to “smart” software. In that case, the crazy eccentric could be on the beam.
Stephen E Arnold, June 11, 2024
A Cultural Black Hole: Lost Data
May 22, 2024
This essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.
A team in Egypt discovered something mysterious near the pyramids. I assume National Geographic will dispatch photographers. Archeologists will probe. Artifacts will be discovered. How much more is buried under the surface of Giza? People have been digging for centuries, and their efforts are rewarded. But what about the artifacts of the digital age?
Upon opening the secret chamber, the digital construct explains to the archeologist from the future that there is a little problem getting the digital information. Thanks, MSFT Copilot.
My answer is, “Yeah, good luck.” The ephemeral quality of online information means that finding something buried near the pyramid of Djoser is going to be more rewarding than looking for the once findable information about MIC, RAC, and ZPIC on a US government Web site. The same void exists for quite a bit of human output captured in now-disappeared systems like The Point (Top 5% of the Internet) and millions of other digital constructs.
A survey report conducted by the Pew Research Center highlights link rot. The idea is simple. Click on a link and the indexed or pointed to content cannot be found. “When Online Content Disappears” has a snappy subtitle:
38 percent of Web pages that existed in 2013 are no longer accessible a decade later.
Wait, are national libraries like the Library of Congress supposed to keep “information.” What about the National Archives? What about the Internet Archive (an outfit busy in court)? What about the Google? (That’s the “all” the world’s information, right?) What about Bibliothèque nationale de France with its rich tradition of keeping French information?
News flash. Unlike the fungible objects unearthed in Egypt, data archeologists are going to have to buy old hard drives on eBay, dig through rubbish piles in “recycling” facilities, or scour yard sales for old machines. Then one has to figure out how to get the data. Presumably smart software can filter through the bits looking for useful data. My suggestion? Don’t count on this happening?
Here are several highlights from the Pew Report:
- Some 38% of webpages that existed in 2013 are not available today, compared with 8% of pages that existed in 2023.
- Nearly one-in-five tweets are no longer publicly visible on the site just months after being posted.
- 21% of all the government webpages we examined contained at least one broken link… Across every level of government we looked at, there were broken links on at least 14% of pages; city government pages had the highest rates of broken links.
The report presents a picture of lost data. Trying to locate these missing data will be less fruitful than digging in the sands of Egypt.
The word “rot” is associated with decay. The concept of “link rot” complements the business practices of government agencies and organizations once gathering, preserving, and organizing data. Are libraries at fault? Are regulators the problem? Are the content creators the culprits?
Sure, but the issue is that as the euphoria and reality of digital information slosh like water in a swimming pool during an earthquake, no one knows what to do. Therefore, nothing is done until knee jerk reflexes cause something to take place. In the end, no comprehensive collection plan is in place for the type of information examined by the Pew folks.
From my vantage point, online and digital information are significant features of life today. Like goldfish in a bowl, we are not able to capture the outputs of the digital age. We don’t understand the datasphere, my term for the environment in which much activity exists.
The report does not address the question, “So what?”
That’s part of the reason future data archeologists will struggle. The rush of zeros and ones has undermined information itself. If ignorance of these data create bliss, one might say, “Hello, Happy.”
Stephen E Arnold, May 22, 2023
E2EE: Not Good Enough. So What Is Next?
May 21, 2024
This essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.
What’s wrong with software? “
I think one !*#$ thing about the state of technology in the world today is that for so many people, their job, and therefore the thing keeping a roof over their family’s head, depends on adding features, which then incentives people to, well, add features. Not to make and maintain a good app.
Who has access to the encrypted messages? Someone. That’s why this young person is distraught as she is escorted to the police van. Thanks, MSFT Copilot. Good enough.
This statement appears in “A Rant about Phone Messaging Apps UI.” But there are some more interesting issues in messaging; specifically, E2EE or end to end encrypted messaging. The current example of talking about the wrong topic in a quite important application space is summarized in Business Insider, an estimable online publication with snappy headlines like this one: “”In the Battle of Telegram vs Signal, Elon Musk Casts Doubt on the Security of the App He Once Championed.” That write up reports as “real” news:
Signal has also made its cryptography open-source. It is widely regarded as a remarkably secure way to communicate, trusted by Jeff Bezos and Amazon executives to conduct business privately.
I want to point out that Edward Snowden “endorses” Signal. He does not use Telegram. Does he know something that others may not have tucked into their memory stack?
The Business Insider “real” news report includes this quote from a Big Dog at Signal:
“We use cryptography to keep data out of the hands of everyone but those it’s meant for (this includes protecting it from us),” Whittaker wrote. “The Signal Protocol is the gold standard in the industry for a reason–it’s been hammered and attacked for over a decade, and it continues to stand the test of time.”
Pavel Durov, the owner of Telegram, and the brother of the person like two Ph.D.’s (his brother Nikolai), suggests that Signal is insecure. Keep in mind that Mr. Durov has been the subject of some scrutiny because after telling the estimable Tucker Carlson that Telegram is about free speech. Why? Telegram blocked Ukraine’s government from using a Telegram feature to beam pro-Ukraine information into Russia. That’s a sure-fire way to make clear what country catches Mr. Durov’s attention. He did this, according to rumors reaching me from a source with links to the Ukraine, because Apple or maybe Google made him do it. Blaming the alleged US high-tech oligopolies is a good red herring and a sinky one at that.
What Telegram got to do with the complaint about “features”? In my view, Telegram has been adding features at a pace that is more rapid than Signal, WhatsApp, and a boatload of competitors. have those features created some vulnerabilities in the Telegram set up? In fact, I am not sure Telegram is a messaging platform. I also think that the company may be poised to do an end run around open sourcing its home-grown encryption method.
What does this mean? Here are a few observations:
- With governments working overtime to gain access to encrypted messages, Telegram may have to add some beef.
- Established firms and start ups are nosing into obfuscation methods that push beyond today’s encryption methods.
- Information about who is behind an E2EE messaging service is tough to obtain? What is easy to document with a Web search may be one of those “fake” or misinformation plays.
Net net: E2EE is getting long in the tooth. Something new is needed. If you want to get a glimpse of the future, catch my lecture about E2EE at the upcoming US government Cycon 2024 event in September. Want a preview? We have a briefing. Write benkent2020 at yahoo dot com for restrictions and prices.
Stephen E Arnold, May 21, 2024
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