Intel Speed Data: Horse Feathers from the Horse Ridge Gang
February 12, 2021
Intel is an interesting example of paranoia forgotten. One of the Intel wizards pointed out in a meeting, “I’m paranoid because everyone is out to get me.” I think this expert wrote a book based on this quip. Paranoid outfits have to try harder. Why? Others want to take them out.
AMD has not nailed the pin on the Horse Ridge Gang’s donkey—yet. Intel has managed to flub its fabbing. This failure to be afraid and thus work harder and smarter resulted in the company losing out in the Great CPU Race. Along the way, the company asserted that it had achieved something every quantum computing wannabe needed: A quantum controller chip. At the same time, AMD was putting in long hours trying to figure out how to go smaller, deliver more bang for the computer buck, and reduce its CPUs’ power consumption.
Whilst engaged in the quantum computing gold rush and fab flubbing, Apple did the M1 thing. How does Intel respond to a hippy dippy Silicon Valley outfit? The best way possible for an outfit which had lost the ability to fear what its competitors can do. Intel points out that Apple is pretty much a not-so-serious technology outfit.
You can get the details of this interesting explanation of fab flubbing, missing mobile, and finding itself trying to deal with AMD and Apple. It will be a while before the Horse Ridge thing produces Apple-scale revenues in my opinion.
The write up “Intel Swipes at Apple Silicon with Selective Benchmark Claims” states:
The [Intel presentation] slides generally appear to show Intel’s chip as being either comparable or superior to the M1 in various tasks, though with major caveats. For a start, the benchmarks use Intel’s “Real-world usage guideline” tests, a collection of trials that don’t seem to be actively followed by most other testers.
The article runs through some performance results showing the Horse Ridge Gang has fast horses. I then noted this passage:
While a company aims to present itself and its products in the best light, and potentially in a way that brings competitors down in comparison, Intel’s presentation indicates it is doing so by jumping through hoops. Cherry-picking test results and using more obscure testing procedures than typical suggests Intel is straining to paint itself in the best light.
I know that one can put lipstick on a pig. I was not aware that the Horse Ridge Gang decorated its performance data with stage make up and horse feathers.
Stephen E Arnold, February 12, 2021
Unbotify Detects Bots Operating in Mobile Games
February 12, 2021
As an online gamer, I see bots as cheaters and unfair competition. For game developers, they are sources of lost revenue. It is no surprise that bots have followed gaming onto mobile platforms. VentureBeat discusses one solution in, “Detecting 10 Times More Bots and Stopping Fraud with Behavioral Biometrics.” The article describes the problem:
“Bots interfere directly in the monetization of apps, disrupting in-app purchases and user engagement, creating bad user experiences that are the direct cause of churn in every category, including dating apps and social networks. … In gaming, there are bots that watch the ads, see impressions, click on ads and they install the game over and over again. There are the bots that actually play the game. Players use service solution bots for the games they’re playing to harvest resources so they don’t have to buy them, or invest the time in harvesting themselves. It’s a growing problem, specifically in the last year of the pandemic, he said. More and more games are seeing traction and it’s very natural that if a player likes a game, then they might want to skip all the boring stuff and get leveled up as fast as possible. They can buy cheap bots that do all the leveling for them. Fraudsters use bots to play the game and then sell those aged accounts to players who want to start at an advanced level, skipping earlier levels.”
In-app purchases and advertisements that cannot tempt bots are how many games make their money. Those leveled-up accounts can sell for a pretty (real-world) penny, providing more motivation than simply getting ahead in a game. It is frustrating to developers and players alike. And, of course, the bots grow more sophisticated alongside security measures. So what is a game host to do?
For mobile apps, Unbotify is one option that approaches the issue from a fresh angle—it uses biometric sensors to analyze user behavior. Finger pressure and speed, motion of the device and speed of device movement, even light conditions and battery use can all be collected from a phone’s sensors. The software uses this information to create a profile of the user’s behavior. Deviations from this behavior may indicate a bot is at the wheel. Unbotify’s CEO claims the tool detects 10 times more bots than any other solution they have seen. The company is based in Tel Aviv, Israel, and launched in 2015. Unbotify was acquired by Adjust in 2019.
And with gameification in the future, bots will be there.
Cynthia Murrell, February 12, 2021
IBM: Emphasizing the Big in Big Blue Quantum Computing
February 12, 2021
Did you know a small outfit in China is selling a person quantum computer. Discover Magazine reveals this in “A Desktop Quantum Computer for Just $5,000.” This means quantum computers will be crunching Excel spreadsheets for those with terminal spreadsheet fever.
But one must think big. I read “IBM Promises 100x Faster Quantum Computers through New Software Foundations.” The write up explains that Big Blue has gone big, quantumly speaking, of course:
IBM unveiled on Wednesday improvements to quantum computing software that it expects will increase performance of its complex machines by a factor of 100, a development that builds on Big Blue’s progress in making the advanced computing hardware. In a road map, the computing giant targeted the release of quantum computing applications over the next two years that will tackle challenges such as artificial intelligence and complex financial calculations. And it’s opening up lower level programming access that it expects will lead to a better foundation for those applications.
Imagine how much better Watson will perform with more quantum horsepower at its disposal.
But there’s more. The write up explains in a content marketing manner:
IBM is working on increasing the number of qubits in its quantum computers, from 27 in today’s “Falcon” to 1,121 in its “Condor” systems due in 2023. IBM expects in 2024 to investigate a key quantum computing technology called error correction that could make qubits much more stable and therefore capable, Jay Gambetta, IBM’s quantum computing vice president, said in a video.
And the source of this revelation? IBM, of course. The future is just two years away. Sounds good. Now how about revenue growth, explaining how the Palantir tie up will work, and when Watson will deliver on that promise of a billion in revenue from cognitive computing?
Stephen E Arnold, January 12, 2021
Amazon AWS EC2 Pricing
February 11, 2021
Amazon AWS makes many things simple: Off the shelf machine learning models, buying cables, and spending money. If you want to get a sense for the complexity of pricing at AWS, take a look at “EC2 Instances.Info: Easy Amazon ED2 Instance Comparison.” The effort required to compile the table was significant. In addition to the data structured by EC service, region, and other tags — there’s the splash page table itself. Impressive. For those with some financial and technical expertise, a new job category now exists: Figuring out AWS pricing for a project and then determining how to minimize costs over time. From the Amazon one click patent to this pricing inventory. How far has Amazon driven the Bezos bulldozer? A long way.
Stephen E Arnold, February 11, 2021
Google and Broad Match
February 11, 2021
I read “Google Is Moving on From Broad Match Modifier.” The essay’s angle is search engine optimization; that is, spoofing Google’s now diluted relevance methods. The write up says:
Google says it has been getting better at learning the intent behind a query, and is therefore more confident it can correctly map advertisements to queries. As that ability improves, the differences between Phrase Match and Broad Match Modified diminishes. Moving forward, there will be three match types, each with specific benefits:
- Exact match: for precision
- Broad match: for reach
- Phrase match: in Google’s words, to combine the best of both.
Let’s assume that these are the reasons. Exact match delivers precision. Broad match casts a wide net. No thumbtypers wants a null set. Obviously there is zero information in a null set in the mind of the GenXers and Millennials, right? The phrase match is supposed to combine precision and recall. Oh, my goodness, precision and recall. What happened to cause the Google to reach into the deep history of STAIRS III and RECON for this notion.
Google hasn’t and won’t.
The missing factor in the write up’s analysis is answering the question, “When will each of the three approaches be used, under what conditions, and what happens if the bus drives to the wrong city?” (This bus analogy is my happy way of expressing the idea that Google search results often have little to do with either the words in the user’s query or the “intent” of the user (allegedly determined by Google’s knowledge of each user and the magic of more than 100 “factors” for determining what to present).
The key is the word “reach.” Changes to Google’s methods are, from my point of view, are designed to accomplish one thing: Burn through ad inventory.
By killing off functioning Boolean, deprecating search operators, ignoring meaningful time indexing, and tossing disambiguation into the wind blowing a Google volleyball into Shoreline traffic — the company’s core search methods have been shaped to produce money.
SEO experts don’t like this viewpoint. Google doesn’t care as long as the money keeps flowing. With Google investing less in infrastructure and facing significant pressure from government investigators and outfits like Amazon and Facebook, re-explaining search boils down to showing content which transports ads.
Where’s that leave the SEO experts? Answer: Ad sales reps for the Google. Traffic comes to advertisers. But the big bucks are the big advertisers’ campaigns which expose a message to as many eyeballs as possible. That’s why “broad reach” is the fox in the relevance hen house.
Stephen E Arnold, February 11, 2021
AI Success: A Shocking Omission?
February 11, 2021
I read “Here’s What All Successful AI Startups Have in Common.” The “all” troubles me. Plus when I received a copy of the CBInsights’ report, I did not read it. Sorry. Logo collections don’t do it for me.
I noted this statement in the “all” article:
I think “AI startup” is a misnomer when applied to many of the companies included in the CB Insights list because it puts too much focus on the AI side and too little on the other crucial aspects of the company. Successful companies start by addressing an overlooked or poorly solved problem with a sound product strategy. This gives them the minimum market penetration needed to establish their business model and gather data to gain insights, steer their product in the right direction, and train machine learning models. Finally, they use AI as a differentiating factor to solidify their position and maintain the edge over competitors. No matter how advanced, AI algorithms alone don’t make a successful startup nor a business strategy.
What was the shocking omission? The massive amount of jargon and marketing hoo hah each firm generates. I wonder, “Why that point was overlooked?” Oh, there is another common factor too: Reliance on the same small set of methods most AI firms share. Thank you, Reverend Bayes.
Stephen E Arnold, February 11, 2021
Useful No Cost Book about Algorithms
February 11, 2021
If you find math books interesting, you will want to take a look at Jeff Erikson’s Algorithms. The text complements courses the author conducted at the University of Illinois. I enjoyed the section called “Greedy Algorithms,” and there are other useful sections as well, including the discuss of search. The book contains illustrations and exercises. However, the reader will not find answers to these. This page provides links to other material developed for students by the author. The text consumes more than 450 pages. Very useful information.
Stephen E Arnold, February 11, 2021
2021: A Year with Two Gulps of Failure
February 11, 2021
I provide additional commentary on Microsoft’s late January 2021 about the SolarWinds’ misstep. The glitch seems to be like an ink stain. Over time, it spreads: China’s alleged involvement, one third of the security penetrations not involving SolarWinds’ software, and mounting suggestions about how long the bad actors were probing and possibly implanting backdoors in government agencies, big contractors, and commercial enterprises. You can view the video on this blog’s home page on January 9, 2021. For today (Monday, January 8, 2021) I want to call attention to two items.
The first is a useful list of situations in which malware, viruses, and other bad actor actions are not detected. You can find the list in “Why Antivirus Software Fails to Detect Latest Viruses and Malwares.” What’s interesting about the article is that none of the suggestions solves the problem of the Saturday Night Live / Donald Rumsfeld quip, “You don’t know what you don’t know.”
The second is the allegedly accurate information in the ABC News’s report “Former Capitol Police Chief Steven Sund Says Entire Intelligence Community Missed Signs of Riot.” Here’s a passage the Capitol Police’s former top dog to Ms. Pelosi included in the news story:
“Having previously handled two major post-election demonstrations successfully utilizing an action plan that was based on intelligence assessments that had proven to be credible, reliable, and accurate, we reasonably assumed the intelligence assessment for Jan. 6, 2021, was also correct.”
What this means to me is that the intel was off the mark.
Perhaps the SolarWinds’ misstep is the result of several factors. Let me raise these as possibilities:
First, the software designed to identify and flag breaches did not work. Furthermore, the infrastructure in wide use for Microsoft software was the carrier of the malware. No one noticed for possibly a year or more. FireEye investigated a mobile phone access issue and came across the multi-part, multi-stage attack. The breach was not one outfit. The penetration extended to as many as 18,000 organizations. It is not clear what the bad actor did once access to this gold mine of systems was achieved.
Second, the intelligence apparatus of multiple US entities did not characterize the scale, intent, and size of the “friendly” protest at the US Capitol in early January. If the information in the ABC News’s story is accurate, the intelligence reports, like the awareness of the SolarWinds’ misstep, were wide of the mark. Maybe in someplace like Cuba or Bali, just not in the Capitol Police’s tactical planning unit’s hands?
The conclusion is that I see two types of failure with a common root cause: A certain blindness.
Marketing, threat assessment webinars, and licensing existing cyber security software won’t address these, possibly inter related problems.
Not good. Marketing explanations are much better. The fix? Another BrightTALK cyber security briefing, more Microsoft security blog posts, and more security podcasts from former government security attorneys?
Stephen E Arnold, January 11, 2021
Business Intelligence, Expectations, and Data Fog
February 10, 2021
Business intelligence and government intelligence software promises real time data intake, analysis and sense making, and outputs with a mouse click. Have you heard the phrase, “I have the Brooklyn Bridge for sale”? Sure, sure, I know I don’t want to own the Brooklyn Bridge, but that super spiffy intelligence software (what I call intelware), count me in.
The marketing pitch for business intelligence and general intelligence software has not changed significantly over the years. In my experience, a couple of nifty outputs like a relationship diagram and a series of buttons set up to spit out “actionable intelligence” often close the deal. The users of the software usually discover three points not making up a large part of the demos, the discussions, and the final contract for the customer’s requirements.
I read “The Age Of Continuous Business Intelligence.” The idea is appealing. Lots of information and no time to read, review, digest, analyze, and discuss the available information. In my opinion, the attitude now is “I don’t have time.”
Yep, time.
The write up asserts:
we [an outfit called KX] know that shortening the time it takes to ingest, store, process, and analyze historic and real-time data is a game changer for businesses in all sectors. Our customers in finance, manufacturing, automotive, telecommunications and utilities tell us that when processes and systems are continuously fed by real-time data that is enriched by the context of historic data, they can automate critical business decisions resulting in significant operational and commercial benefits.
The write up contains a diagram which lays bare “continuous business intelligence.”
The write up concludes:
As the research clearly shows, real-time data analytics is a critical area of investment for many firms. To ensure maximum value is derived from these investments, it is imperative that organizations – regardless of size and sector – challenge their understanding of what real-time means. By implementing a strategy of continuous business intelligence, firms can dramatically reduce the time it takes to uncover and act on insights that can materially change the game in terms of growth, efficiency and profitability.
I love that “research clearly shows.” The challenges for the continuous thing include:
- Defining real time. (According to research my team did for a project years ago, there are numerous definitions of real time, and there is a Grand Canyon sized gap among these.)
- Making clear the computational short cuts necessary to process “fire hoses”. (Yep, these compromises have a significant impact on costs, validity of system outputs, and the mechanisms for issuing meaningful outputs from sense making.)
- Managing the costs. (Normalizing, verifying, processing, storing, and moving data require human and machine resources. Right, those things.)
Net net: Software whether for business or government applications in intelligence work only if the focus is narrow and the expectations of a wild and crazy MBA are kept within a reality corral. Otherwise, business intelligence will shoot blanks, not silver bullets.
Oh, KX is hooked up with a mid tier consulting firm. What’s that mean? A sudden fog has rolled in, and it is an expensive fog.
Stephen E Arnold, February 10, 2021
Terrorized Publishers Try a New Poison Dart on the Google
February 10, 2021
Google has reduced its investment in plumbing. It’s mostly waffled and fumbled its push into online games. The company has failed to keep Loon balloons aloft. And, more disappointingly, the Google has not solved death. Amazon and Facebook, despite protestations to the contrary, are making progress in online advertising. And the Bezos bulldozer’s new driver knows that product searches are Amazon’s personal turf.
Another group, however, wants to pour poison in Googzilla’s ear. The publishers, aided by their advisors, and assorted governments may have found a way. The write up “EU Ready to Follow Australia’s Lead on Making Big Tech Pay for News” reports:
EU lawmakers overseeing new digital regulation in Europe want to force Big Tech companies to pay for news, echoing a similar move in Australia and strengthening the hand of publishers against Google and Facebook.
Note that this article is behind a paywall, and in order to access it, you have to snag a wonky orange copy or fork over some cash. Very European, eh?
What happens if countries require Google to pay for news? What happens if the millennials holding elected and appointed positions don’t buy the threat of blocking search or killing access to Android apps (hopefully those which distribute malware via the Google Play service)? What if the bold push by Google Australia’s wizardly manager is recognized as a company acting like a country, maybe like the nation state in “The Mouse That Roared”?
Let’s see. Google has been involved in doing its brand of “not evil” for information for about 20 years and change. It takes a long time to develop an economic poison. Too bad the governments were not into the “warp speed” approach to innovation.
And France and its Googley tie up? Ah, France.
Stephen E Arnold, February 10, 2021
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