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Very frustrating for companies who actually do use machine learning to solve a problem! Hard to rise above the background "AI noise" of well-funded marketing.

by Radim 8y ago

Very frustrating for companies who actually do use machine learning to solve a problem! Hard to rise above the background "AI noise" of well-funded marketing. And people are already fed up with all the AI marketing bullshit; "ebbing tide sinks all boats". One way is to offer real-time results via APIs or demos, which cannot be faked with humans due to sheer latency / volume. Another is to be active in the ML community (open source etc) to build a reputation. But there the audience is different (technical), and may not overlap with the business case much.

foobiekr 8y ago
In times of funding plenty the valley is awash with companies that are basically faking it. This was very common in the previous valley bubbles, the Real-Intelligence-Masquerading-As-Artificial thing is just one in a long line of semi-frauds that the valley tends to accumulate. In the 90s the flood of B2B companies was as crazy as the current flood of AI companies. This will pass when funding gets tight again and/or the economy enters a recession. A very sharp recession is actually good for the valley because it helps clean out the fakers; it's no different than the first cold snap in the winter helping clear away certain pests. (One takeaway from this is that if one wants to found a startup, and one is not a fraud, it's actually better in almost every way to do so in the first part of a recession: lower salaries, less grass-is-greener attrition, lower real estate costs, etc.)
- blablabla123 8y ago
  It's crazy when you consider that the Lean Startup advocates in the past actually advocated to fake things. For outsiders it's virtually impossible to tell if something is real or not.
blensor 8y ago
A company that needs to be protected from the market to be successful in this very same market, isn't this a fallacy? Trying to create a startup that can't at least compete with the existing solutions isn't a very good business strategy in my opinion. That's what academia is for. Research that is still too far away from being profitable but that has it's merits in the long run.
- msg3 8y ago
  Not really - Korea protected Samsung et al for years before they were capable of competing globally.
  - sparkie 8y ago
    Also, many of the largest internet businesses in China started out as cheap imitations of western websites, but gained success as the western versions were blocked by the great firewall. The Chinese government has basically propped up their own industries by shutting out the west, and are now screaming about "protectionism" when the west is finally responding.
- sesqu 8y ago
  The claim is that there may be a market for AI-powered technologies, but that market is suppressed by non-AI competitors exploiting information asymmetry.
  - justtopost 8y ago
    Wouldn't that suggest however that AI is not the best tool for the job? AI should be the great equalizer if the tech actually was useful, but I have seen precious few examples. The usual triumphs are almost all actually human sourced and then delivered by algo. (google image, etc.)
    - TeMPOraL 8y ago
      No, the point is that dishonest marketing distorts the market. The companies use human labour to deliver useful services, but falsely advertise as AI-driven to capitalize on the novelty factor. This makes life more difficult for both companies delivering the same service, but advertising honestly, and for companies actually trying to deliver the product by means of AI. The result is that money flows to dishonest people, instead of honest people and/or people actually trying to push technology forward.
    - obastani 8y ago
EpicEng 8y ago
>Very frustrating for companies who actually do use machine learning to solve a problem! I get that on a purely technical level, but really... who cares about the implementation? If a company is solving problems it really doesn't matter, and if they're solving it better using some mix of ML and human intervention... again; who cares?
- JabavuAdams 8y ago
  Anyone who's betting on the growth of the company. Hiring more and more humans doesn't scale as well as automating tasks.
AJ007 8y ago
There are two sides to this -- AI used a marketing buzzword to attract customers and AI used as a buzzword to attract investors. For the customers, they need to be sure that the company is actually capable of solving the problem they are claiming to solve (before signing some sort of long term contract that doesn't actually make the claims the sales people put forward.) The customer's evaluation, however is distinct from that of an investors. It is the job of an investor to determine if the startup is actually capable of having reasonable odds of successfully pursuing whatever they are claiming to be doing. If an investor is not, then for an actual startup doing machine learning, probably this is not they type of investor you want. During the ICO pump and dump cycle one thing stuck out to me - nearly all of the ICOs were being run by people without any cryptography experience. Most had little to no software development experience. I'd suggest investors take their first step in evaluating "AI" startups similarly.

by Radim 8y ago

foobiekr 8y ago

In times of funding plenty the valley is awash with companies that are basically faking it. This was very common in the previous valley bubbles, the Real-Intelligence-Masquerading-As-Artificial thing is just one in a long line of semi-frauds that the valley tends to accumulate. In the 90s the flood of B2B companies was as crazy as the current flood of AI companies. This will pass when funding gets tight again and/or the economy enters a recession. A very sharp recession is actually good for the valley because it helps clean out the fakers; it's no different than the first cold snap in the winter helping clear away certain pests. (One takeaway from this is that if one wants to found a startup, and one is not a fraud, it's actually better in almost every way to do so in the first part of a recession: lower salaries, less grass-is-greener attrition, lower real estate costs, etc.)

blablabla123 8y ago
It's crazy when you consider that the Lean Startup advocates in the past actually advocated to fake things. For outsiders it's virtually impossible to tell if something is real or not.

blensor 8y ago

A company that needs to be protected from the market to be successful in this very same market, isn't this a fallacy? Trying to create a startup that can't at least compete with the existing solutions isn't a very good business strategy in my opinion. That's what academia is for. Research that is still too far away from being profitable but that has it's merits in the long run.

msg3 8y ago
Not really - Korea protected Samsung et al for years before they were capable of competing globally.
- sparkie 8y ago
  Also, many of the largest internet businesses in China started out as cheap imitations of western websites, but gained success as the western versions were blocked by the great firewall. The Chinese government has basically propped up their own industries by shutting out the west, and are now screaming about "protectionism" when the west is finally responding.
sesqu 8y ago
The claim is that there may be a market for AI-powered technologies, but that market is suppressed by non-AI competitors exploiting information asymmetry.
- justtopost 8y ago
  Wouldn't that suggest however that AI is not the best tool for the job? AI should be the great equalizer if the tech actually was useful, but I have seen precious few examples. The usual triumphs are almost all actually human sourced and then delivered by algo. (google image, etc.)
  - TeMPOraL 8y ago
    No, the point is that dishonest marketing distorts the market. The companies use human labour to deliver useful services, but falsely advertise as AI-driven to capitalize on the novelty factor. This makes life more difficult for both companies delivering the same service, but advertising honestly, and for companies actually trying to deliver the product by means of AI. The result is that money flows to dishonest people, instead of honest people and/or people actually trying to push technology forward.
  - obastani 8y ago

EpicEng 8y ago

>Very frustrating for companies who actually do use machine learning to solve a problem! I get that on a purely technical level, but really... who cares about the implementation? If a company is solving problems it really doesn't matter, and if they're solving it better using some mix of ML and human intervention... again; who cares?

JabavuAdams 8y ago
Anyone who's betting on the growth of the company. Hiring more and more humans doesn't scale as well as automating tasks.

AJ007 8y ago

There are two sides to this -- AI used a marketing buzzword to attract customers and AI used as a buzzword to attract investors. For the customers, they need to be sure that the company is actually capable of solving the problem they are claiming to solve (before signing some sort of long term contract that doesn't actually make the claims the sales people put forward.) The customer's evaluation, however is distinct from that of an investors. It is the job of an investor to determine if the startup is actually capable of having reasonable odds of successfully pursuing whatever they are claiming to be doing. If an investor is not, then for an actual startup doing machine learning, probably this is not they type of investor you want. During the ICO pump and dump cycle one thing stuck out to me - nearly all of the ICOs were being run by people without any cryptography experience. Most had little to no software development experience. I'd suggest investors take their first step in evaluating "AI" startups similarly.