Kagi Search Beat Down

April 17, 2024

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

People surprise me. It is difficult to craft a search engine. Sure, a recent compsci graduate will tell you, “Piece of cake.” It is not. Even with oodles of open source technology, easily gettable content, and a few valiant individuals who actually want relevant results — search and retrieval are tough to get right. The secret to good search, in my opinion, is to define a domain, preferably a technical field, identify the relevant content, obtain rights, if necessary, and then do the indexing and the other “stuff.”

In my experience, it is a good idea to have either a friend with deep pockets, a US government grant (hello, NSF, said Google decades ago), or a credit card with a hefty credit line. Failing these generally acceptable solutions, one can venture into the land of other people’s money. When that runs out or just does not work, one can become a pay-to-play outfit. We know what that business model delivers. But for a tiny percentage of online users, a subscription service makes perfect sense. The only problem is that selling subscriptions is expensive, and there is the problem of churn. Lose a customer and spend quite a bit of money replacing that individual. Lose big customers spend oodles and oodles of money replacing that big spender.

I read “Do Not Use Kagi.” This, in turn, directed me to “Why I Lost Faith in Kagi.” Okay, what’s up with the Kagi booing? The “Lost Faith” article runs about 4,000 words. The key passage for me is:

Between the absolute blasé attitude towards privacy, the 100% dedication to AI being the future of search, and the completely misguided use of the company’s limited funds, I honestly can’t see Kagi as something I could ever recommend to people.

I looked at Kagi when it first became available, and I wrote a short email to the “Vlad” persona. I am not sure if I followed up. I was curious about how the blend of artificial intelligence and metasearch was going to deal with such issues as:

  1. Deduplication of results
  2. Latency when a complex query in a metasearch system has to wait for a module to do it thing
  3. How the business model was going to work: Expensive subscription, venture funding, collateral sales of the interface to law enforcement, advertising, etc..
  4. Controlling the cost of the pings, pipes, and power for the plumbing
  5. Spam control.

I know from experience that those dabbling in the search game ignore some of my routine questions. The reasons range from “we are smarter than you” to “our approach just handles these issues.”

image

Thanks, MSFT Copilot. Recognize anyone in the image you created?

I still struggle with the business model of non-ad supported search and retrieval systems. Subscriptions work. Well, they worked out of the gate for ChatGPT, but how many smart search systems do I want to join? Answer: Zero.

Metasearch systems are simply sucker fish on the shark bodies of a Web search operator. Bing is in the metasearch game because it is a fraction of the Googzilla operation. It is doing what it can to boost its user base. Just look at the wonky Edge ads and the rumored miniscule gain the additional of smart search has delivered to Bing traffic. Poor Yandex is relocating and finds itself in a different world from the cheerful environment of Russia.

Web content indexing is expensive, difficult, and tricky.

But why pick on Kagi? Beats me. Why not write about dogpile.com, ask.com, the duck thing, or startpage.com (formerly ixquick.com)? Each embodies a certain subsonic vibe, right?

Maybe it is the AI flavor of Kagi? Maybe it is the amateur hour approach taken with some functions? Maybe it is just a disconnect between an informed user and an entrepreneurial outfit running a mile a minute with a sign that says, “Subscribe”?

I don’t know, but it is interesting when Web search is essentially a massive disappointment that some bright GenX’er has not figured out a solution.

Stephen E Arnold, April 17, 2024

HP and Autonomy: The Long Tail of Search and Retrieval

April 8, 2024

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

The US justice system is flawed but when big money is at stake, it quickly works as it’s supposed to do. British tech entrepreneur is responsible for making the tech industry lose a lot of greenbacks and the BBC shares the details: “Mike Lynch: Autonomy Founder’s Fraud Trial Begins In The US.” Lynch, formerly called Britain’s equivalent of Bill Gates, was extradited to the US in 2023 after a British court found him guilty of a civil fraud cause. He is accused of over inflating the value of his former company Autonomy. Autonomy was sold to Hewlett-Packard (HP) in 2011 for $11 billion.

Lynch is facing sixteen charges and a possible twenty-five years in prison if convicted. Reid Weingarten, Lynch’s attorney, stated his client is prepared to take the stand. He also said that Lynch focused on Autonomy’s technology side and left the finances to others. After buying Autonomy, HP valued it at $2.2 billion and claimed Lynch duped them.

Lynch founded Autonomy in 1996 and it became a top 100 public companies in the United Kingdom. Autonomy was known for software that extracted information from unstructured content: video, emails, and phone calls.

HP is not mincing claims in this case:

“US prosecutors in San Francisco say Mr Lynch backdated agreements to mislead about the company’s sales; concealed the firm’s loss-making business reselling hardware; and intimidated or paid off people who raised concerns, among other claims. In court filings, his attorneys have argued that the "real reason for the write-down" was a failure by HP to manage the merger. ‘Then, with its stock price crumbling under the weight of its own mismanagement, circled the wagons to protect its new leaders and wantonly accused’ Mr Lynch of fraud, they wrote.”

London’s High Court convicted Lynch and Autonomy’s former CFO Sushovan Hussain of fraud. Hussain was imprisoned for five years and fined millions of dollars. The pair claimed HP’s case against them was buyer’s remorse and management failings.

Lynch should be held accountable for false claims, pay the fines, and be jailed if declared guilty. If the court does convict him, it will be time for more legal gymnastics.

Whitney Grace, April 8, 2024

Finding Live Music Performances

April 5, 2024

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

Here is a niche search category some of our readers will appreciate. Lifehacker shares “The Best Ways to Find Live Gigs for Music You Love.” Writer David Nield describes how one can tap into a combination of sources to stay up to date on upcoming music events. He begins:

“More than once I’ve missed out on shows in my neighborhood put on by bands I like, just because I’ve been out of the loop. Whether you don’t want to miss gigs by artists you know, or you’re keen to get out and discover some new music, there are lots of ways to stay in touch with the live shows happening in your area—you need never miss a gig again. Pick the one(s) that work best for you from this list.”

First are websites dedicated to spreading the musical word, like Songkick and Bandsintown. One can sign up for notices or simply browse the site by artist or location. These sites can also use one’s listening data from streaming apps to inform their results. Or one can go straight to the source and follow artists on social media or their own websites (but that can get overwhelming if one enjoys many bands). Several music apps like Spotify and Deezer will notify you of upcoming concerts and events for artists you choose. Finally, YouTube lists tour details and ticket links beneath videos of currently touring bands, highlighting events near you. If, that is, you have chosen to share your location with the Google-owned site.

Cynthia Murrell, April 5, 2024

Is the AskJeeves Approach the Next Big Thing Again?

March 14, 2024

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

Way back when I worked in silicon Valley or Plastic Fantastic as one 1080s wag put it, AskJeeves burst upon the Web search scene. The idea is that a user would ask a question and the helpful digital butler would fetch the answer. This worked for questions like “What’s the temperature in San Mateo?” The system did not work for the types of queries my little group of full-time equivalents peppered assorted online services.

image

A young wizard confronts a knowledge problem. Thanks, MSFT Copilot. How’s that security today? Okay, I understand. Good enough.

The mechanism involved software and people. The software processed the query and matched up the answer with the outputs in a knowledge base. The humans wrote rules. If there was no rule and no knowledge, the butler fell on his nose. It was the digital equivalent of nifty marketing applied to a system about as aware as the man servant in Kazuo Ishiguro’s The Remains of the Day.

I thought about AskJeeves as a tangent notion as I worked through “LLMs Are Not Enough… Why Chatbots Need Knowledge Representation.” The essay is an exploration of options intended to reduce the computational cost, power sucking, and blind spots in large language models. Progress is being made and will be made. A good example is this passage from the essay which sparked my thinking about representing knowledge. This is a direct quote:

In theory, there’s a much better way to answer these kinds of questions.

  1. Use an LLM to extract knowledge about any topics we think a user might be interested in (food, geography, etc.) and store it in a database, knowledge graph, or some other kind of knowledge representation. This is still slow and expensive, but it only needs to be done once rather than every time someone wants to ask a question.
  2. When someone asks a question, convert it into a database SQL query (or in the case of a knowledge graph, a graph query). This doesn’t necessarily need a big expensive LLM, a smaller one should do fine.
  3. Run the user’s query against the database to get the results. There are already efficient algorithms for this, no LLM required.
  4. Optionally, have an LLM present the results to the user in a nice understandable way.

Like AskJeeves, the idea is a good one. Create a system to take a user’s query and match it to information answering the question. The AskJeeves’ approach embodied what I called rules. As long as one has the rules, the answers can be plugged in to a database. A query arrives, looks for the answer, and presents it. Bingo. Happy user with relevant information catapults AskJeeves to the top of a world filled with less elegant solutions.

The question becomes, “Can one represent knowledge in such a way that the information is current, usable, and “accurate” (assuming one can define accurate). Knowledge, however, is a slippery fish. Small domains with well-defined domains chock full of specialist knowledge should be easier to represent. Well, IBM Watson and its adventure in Houston suggests that the method is okay, but it did not work. Larger scale systems like an old-fashioned Web search engine just used “signals” to produce lists which presumably presented answers. “Clever,” correct? (Sorry, that’s an IBM Almaden bit of humor. I apologize for the inside baseball moment.)

What’s interesting is that youthful laborers in the world of information retrieval are finding themselves arm wrestling with some tough but elusive problems. What is knowledge? The answer, “It depends” does not provide much help. Where does knowledge originate, the answer “No one knows for sure.” That does not advance the ball downfield either.

Grabbing epistemology by the shoulders and shaking it until an answer comes forth is a tough job. What’s interesting is that those working with large language models are finding themselves caught in a room of mirrors intact and broken. Here’s what TheTemples.org has to say about this imaginary idea:

The myth represented in this Hall tells of the divinity that enters the world of forms fragmenting itself, like a mirror, into countless pieces. Each piece keeps its peculiarity of reflecting the absolute, although it cannot contain the whole any longer.

I have no doubt that a start up with venture funding will solve this problem even though a set cannot contain itself. Get coding now.

Stephen E Arnold, March 14, 2024

Kagi Hitches Up with Wolfram

March 6, 2024

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

Kagi + Wolfram” reports that the for-fee Web search engine with AI has hooked up with one of the pre-eminent mathy people innovating today. The write up includes PR about the upsides of Kagi search and Wolfram’s computational services. The article states:

…we have partnered with Wolfram|Alpha, a well-respected computational knowledge engine. By integrating Wolfram Alpha’s extensive knowledge base and robust algorithms into Kagi’s search platform, we aim to deliver more precise, reliable, and comprehensive search results to our users. This partnership represents a significant step forward in our goal to provide a search engine that users can trust to find the dependable information they need quickly and easily. In addition, we are very pleased to welcome Stephen Wolfram to Kagi’s board of advisors.

image

The basic wagon gets a rethink with other animals given a chance to make progress. Thanks, MSFT Copilot. Good enough, but in truth I gave up trying to get a similar image with the dog replaced by a mathematician and the pig replaced with a perky entrepreneur.

The integration of mathiness with smart search is a step forward, certainly more impressive than other firms’ recycling of Web content into bubble gum cards presenting answer. Kagi is taking steps — small, methodical ones — toward what I have described as “search enabled applications” and my friend Dr. Greg Grefenstette described in his book with the snappy title “Search-Based Applications: At the Confluence of Search and Database Technologies (Synthesis Lectures on Information Concepts, Retrieval, and Services, 17).”

It may seem like a big step from putting mathiness in a Web search engine to creating a platform for search enabled applications. It may be, but I like to think that some bright young sprouts will figure out that linking a mostly brain dead legacy app with a Kagi-Wolfram service might be useful in a number of disciplines. Even some super confident really brilliantly wonderful Googlers might find the service useful.

Net net: I am gratified that Kagi’s for-fee Web search is evolving. Google’s apparent ineptitude might give Kagi the chance Neeva never had.

Stephen E Arnold, March 6, 2024

SearXNG: A New Metasearch Engine

March 4, 2024

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

Internet browsers and search engines are two of the top applications used on computers. Search engine giants like Bing and Google don’t respect users’ privacy and they track everything. They create individual user profiles then sell and use the information for targeted ads. The search engines also demote controversial information and return biased search results. On his blog, FlareXes shares a solution that protects privacy and encompasses metasearch: “Build Your Own Private Search Engine With SearXNG.”

SearXNG is an open source, customizable metasearch engine that returns search results from multiple sources and respects privacy. It was originally built off another open source project SearX. SearXNG has an extremely functional user interface. It also aggregates information from over seventy search engines, including DuckDuckGo, Brave Search, Bing, and Google.

The best thing about SearXNG is protecting user privacy: But perhaps the best thing about SearXNG is its commitment to user privacy. Unlike some search engines, SearXNG doesn’t track users or generate personalized profiles, and it never shares any information with third parties.”

Because SearXNG is a metasearch engine, it supports organic search results. This allows users to review information that would otherwise go unnoticed. That doesn’t mean the returns will allegedly be unbiased. The idea is that SearXNG returns better results than a revenue juggernaut:

SearXNG aggregates data from different search engines that doesn’t mean this could be biased. There is no way for Google to create a profile about you if you’re using SearXNG. Instead, you get high-quality results like Google or Bing. SearXNG also randomizes the results so no SEO or top-ranking will not gonna work. You can also enable independent search engines like Brave Search, Mojeek etc.”

If you want a search engine that doesn’t collect your personal data and has betters search results, warrants a test drive. The installation may require some tech fiddling.

Whitney Grace, March 4, 2024

A Look at Web Search: Useful for Some OSINT Work

February 22, 2024

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

I read “A Look at Search Engines with Their Own Indexes.” For me, the most useful part of the 6,000 word article is the identified search systems. The author, a person with the identity Seirdy, has gathered in one location a reasonably complete list of Web search systems. Pulling such a list together takes time and reflects well on Seirdy’s attention to a difficult task. There are some omissions; for example, the iSeek education search service (recently repositioned), and Biznar.com, developed by one of the founders of Verity. I am not identifying problems; I just want to underscore that tracking down, verifying, and describing Web search tools is a difficult task. For a person involved in OSINT, the list may surface a number of search services which could prove useful; for example, the Chinese and Vietnamese systems.

A generated image based on your input prompt

A new search vendor explains the advantages of a used convertible driven by an elderly person to take a French bulldog to the park once a day. The clueless fellow behind the wheel wants to buy a snazzy set of wheels. The son in the yellow shirt loves the vehicle. What does that car sales professional do? Some might suggest that certain marketers lie, sell useless add ons, patch up problems, and fiddle the interest rate financing. Could this be similar to search engine cheerleaders and the experts who explain them? Thanks ImageFX. A good enough illustration with just a touch of bias.

I do want to offer several observations:

  1. Google dominates Web search. There is an important distinction not usually discussed when some experts analyze Google; that is, Google delivers “search without search.” The idea is simple. A person uses a Google service of which there are many. Take for example Google Maps. The Google runs queries when users take non-search actions; for example, clicking on another part of a map. That’s a search for restaurants, fuel services, etc. Sure, much of the data are cached, but this is an invisible search. Competitors and would-be competitors often forget that Google search is not limited to the Google.com search box. That’s why Google’s reach is going to be difficult to erode quickly. Google has other search tricks up its very high-tech ski jacket’s sleeve. Think about search-enabled applications.
  2. There is an important difference between building one’s own index of Web content and sending queries to other services. The original Web indexers have become like rhinos and white tigers. It is faster, easier, and cheaper to create a search engine which just uses other people’s indexes. This is called metasearch. I have followed the confusion between search and metasearch for many years. Most people do not understand or care about the difference in approaches. This list illustrates how Web search is perceived by many people.
  3. Web search is expensive. Years ago when I was an advisor to BearStearns (an estimable outfit indeed), my client and I were on a conference call with Prabhakar Raghavan (then a Yahoo senior “search” wizard). He told me and my client, “Indexing the Web costs only $300,000 US.” Sorry Dr. Raghavan (now the Googler who made the absolutely stellar Google Bard presentation in France after MSFT and OpenAI caught Googzilla with its gym shorts around its ankles in early 2023) you were wrong. That’s why most “new” search systems look for short cuts. These range from recycling open source indexes to ignoring pesky robots.txt files to paying some money to use assorted also-ran indexes.

Net net: Web search is a complex, fast-moving, and little-understood business. People who know now do other things. The Google means overt search, embedded search, and AI-centric search. Why? That is a darned good question which I have tried to answer in my different writings. No one cares. Just Google it.

PS. Download the article. It is a useful reference point.

Stephen E Arnold, February 22, 2024

OpenAI Embarks on Taking Down the Big Guy in Web Search

February 22, 2024

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

The Google may be getting up there in Internet years; however, due to its size and dark shadow, taking the big fellow down and putting it out of the game may be difficult. Users are accustomed to the Google. Habits, particularly those which become semi automatic like a heroin addict’s fiddling with a spoon, are tough to break. After 25 years, growing out of a habit is reassuring to worried onlookers. But the efficacy of wait-and-see is not  getting a bent person straight.

image

Taking down Googzilla may be a job for lots of little people. Thanks, Google ImageFX. Know thyself, right?

I read “OpenAI Is Going to Face an Uphill Battle If It Takes on Google Search.” The write up describes an aspirational goal of Sam AI-Man’s OpenAI system. The write up says:

OpenAI is reportedly building its own search product to take on Google.

OpenAI is jumping in a CRRC already crowded with special ops people. There is the Kagi subscription search. There is Phind.com and You.com. There is a one-man band called Stract and more. A new and improved Yandex is coming. The reliable Swisscows.com is ruminating in the mountains. The ever-watchful OSINT professionals gather search engines like a mother goose. And what do we get? Bing is going nowhere even with Copilot except in the enterprise market where Excel users are asking, “What the H*ll?” Meanwhile the litigating beast continues to capture 90 percent or more of search traffic and oodles of data. Okay, team, who is going to chop block the Google, a fat and slow player at that?

The write up opines:

But on the search front, it’s still all Google all the way. And even if OpenAI popularized the generative AI craze, the company has a long way to go if it hopes to take down the search giant.

Competitors can dream, plot, innovate, and issue press releases. But for the foreseeable future, the big guy is going to push others out of the way.

Stephen E Arnold, February 22, 2024

Search Is Bad. This Is News?

February 20, 2024

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

Everyone is a search expert. More and more “experts” are criticizing “search results.” What is interesting is that the number of gripes continues to go up. At the same time, the number of Web search options is creeping higher as well. My hunch is that really smart venture capitalists “know” there is a money to be made. There was one Google; therefore, another one is lurking under a pile of beer cans in a dorm somewhere.

One Tech Tip: Ready to Go Beyond Google? Here’s How to Use New Generative AI Search Sites” is a “real” news report which explains how to surf on the new ChatGPT-type smart systems. At the same time, the article makes it clear that the Google may have lost its baseball bat on the way to the big game. The irony is that Google has lots of bats and probably owns the baseball stadium, the beer concession, and the teams. Google also owns the information observatory near the sports arena.

The write up reports:

A recent study by German researchers suggests the quality of results from Google, Bing and DuckDuckGo is indeed declining. Google says its results are of significantly better quality than its rivals, citing measurements by third parties.

A classic he said, she said argument. Objective and balanced. But the point is that Google search is getting worse and worse. Bing does not matter because its percentage of the Web search market is low. DuckDuck is a metasearch system like Startpage. I don’t count these as primary search tools; they are utilities for search of other people’s indexes for the most part.

What’s new with the ChatGPT-type systems? Here’s the answer:

Rather than typing in a string of keywords, AI queries should be conversational – for example, “Is Taylor Swift the most successful female musician?” or “Where are some good places to travel in Europe this summer?” Perplexity advises using “everyday, natural language.” Phind says it’s best to ask “full and detailed questions” that start with, say, “what is” or “how to.” If you’re not satisfied with an answer, some sites let you ask follow up questions to zero in on the information needed. Some give suggested or related questions. Microsoft‘s Copilot lets you choose three different chat styles: creative, balanced or precise.

Ah, NLP or natural language processing is the key, not typing key words. I want to add that “not typing” means avoiding when possible Boolean operators which return results in which stings occur. Who wants that? Stupid, right?

There is a downside; for instance:

Some AI chatbots disclose the models that their algorithms have been trained on. Others provide few or no details. The best advice is to try more than one and compare the results, and always double-check sources.

What’s this have to do with Google? Let me highlight several points which make clear how Google remains lost in the retrieval wilderness, leading the following boy scout and girl scout troops into the fog of unknowing:

  1. Google has never revealed what it indexes or when it indexes content. What’s in the “index” and sitting on Google’s servers is unknown except to some working at Google. In fact, the vast majority of Googlers know little about search. The focus is advertising, not information retrieval excellence.
  2. Google has since it was inspired by GoTo, Overture, and Yahoo to get into advertising been on a long, continuous march to monetize that which can be shaped to produce clicks. How far from helpful is Google’s system? Wait until you see AI helping you find a pizza near you.
  3. Google’s bureaucratic methods is what I would call many small rubber boats generally trying to figure out how to get to Advertising Land, but they are caught in a long, difficult storm. The little boats are tough to keep together. How many AI projects are enough? There are never enough.

Net net: The understanding of Web search has been distorted by Google’s observatory. One is looking at information in a Google facility, designed by Googlers, and maintained by Googlers who were not around when the observatory and associated plumbing was constructed. As a result, discussion of search in the context of smart software is distorted.

ChatGPT-type services provide a different entry point to information retrieval. The user still has to figure out what’s right and what’s wonky. No one wants to do that work. Write ups about “new” systems are little more than explanations of why most people will not be able to think about search differently. That observatory is big; it is familiar; and it is owned by Google just like the baseball team, the concessions, and the stadium.

Search means Google. Writing about search means Google. That’s not helpful or maybe it is. I don’t know.

Stephen E Arnold, February 20, 2024

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Relevance: Rest in Peace

February 16, 2024

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

It is Friday, and I am tired of looking at computer generated news with lines like “Insert paragraphs here”. No, don’t bother. The issues I am experiencing with SmartNews and Flipboard are more than annoyances. These, like other aggregation services, are becoming less productive than reading random Reddit posts or the information posted on Blackmagic forum boards. Everyone is trying to find a way to make a buck before the bank account says, “Yo, transaction denied.”

image

Marketers will find that buying traffic enables many opportunities. Thanks MSFT Copilot whatever. Good enough.

I read “Meta Is Passing on the Apple Tax for Boosted Posts to Advertisers.” What’s the big point in the pontificating online service? How about this passage:

Meta says those who want to boost posts through its iOS apps will now need to add prepaid funds and pay for them before their boosted posts are published. Meta will charge an extra 30 percent to cover Apple’s transaction fee for preloading funds in iOS as well.

My interpretation is: If you want traffic, you will pay for it. And you will pay other fees as well. And if you don’t like it, give those free press release services a whirl.

So what?

  1. The pay-for-traffic model is now the best and fastest way to get traffic or clicks. Free rides, I think, have been replaced with tolls.
  2. Next up will be subscriptions to those who want traffic. Just pay a lump sum and you will get traffic. The traffic may be worthless, but for those who like to play roulette, you may get a winner. Remember the house owns zero and double zero plus whatever you lose. Great deal, right?
  3. The popular click is likely to be shaped, weaponized, or disinformationized.

Net net: Relevance will be quite difficult to define outside of a transactional relationship. Will this matter? Nope because most users accept what a service returns as relevant, accurate, and reliable.

Stephen E Arnold, February 16, 2024

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