waltervj@dartvax.UUCP (walter jeffries) (09/30/87)
I am in the process of starting a company to do expert systems developement in the field of psychiatry. Principles include two top domain experts in this field, an expert in data anlysis, and an MBA canidate with training in marketing in the computer field. I am not the business end of things but would appreciate any comments/experiences that people may have with getting capital (sources, things to be careful of, etc.). Of course, if you want to invest money as well as advice that would be appreciated too :-). Many thanx, -Waltervj@dartvax
chedley@inteloc.intel.com (CHEDLEY) (10/06/87)
In article <7260@dartvax.UUCP> waltervj@dartvax.UUCP (walter jeffries) writes: > >I am not the business end of things but >would appreciate any comments/experiences that people may have with getting >capital (sources, things to be careful of, etc.). Of course, if you want to >invest money as well as advice that would be appreciated too :-). > There are three major sources of money for start-up financing: 1) Money from the owners/starters of the company: In this case it is your and your partners' own savings and personal loans (credit cards, Home equity loans, personal unsecured bank loans,..) MONEY FROM THIS SOURCE IS TYPICALLY INSUFFICIENT TO GET THE BUSINESS ROLLING 2) Venture Capital: This money belongs to funds(*), companies or private individuals who are looking to invest in start-up businesses. In return they require the "ownership" of a portion of the business, along with some other conditions (oversight on the books of the company, a say in management appointments, options on the share of the company if and when it goes public,...etc) MONEY FROM THIS SOURCE IS RELATIVELY AVAILABLE. 3) Govrmt Money (State/Federal) : This is typically an easy conditions loan (low interest rate, long grace period, easy payment schedule..) provided by some state or federal agencies to promote small and start companies. Try to tap this source to the max. And you do not have to be a woman or a member of a minority group to qualify for this cheap source of financing. GOVRNMT MONEY IS THE CHEAPEST SOURCE OF FINANCING START UPS Due to the constraints of the venture capitalist's money, it is advantageous to leverage it as much as possible with the other sources's money. That is, for each dollar from source 1 or 3, get the maximum venture capital you can reach for. (*): There are even a few venture capital mutual funds out there. ..CHEDLEY..
shore@epiwrl.EPI.COM (John Shore) (10/07/87)
In article <7260@dartvax.UUCP> waltervj@dartvax.UUCP (walter jeffries) writes: > >I am in the process of starting a company to do expert systems developement >in the field of psychiatry.... >...(sources, things to be careful of, etc.).... Things to be careful of? Expert systems and AI. js
jbn@glacier.STANFORD.EDU (John B. Nagle) (10/13/87)
Right now, the venture capital community has had it with expert systems.
Hambrecht of Hambrecht and Quist, one of the more influential venture
capitalists, has been quoted as saying "Artificial intelligence is the most
effective means yet invented for separating investors from their money".
There are no AI startup success stories yet, remember; nothing comparable
to SUN or Lotus has happened. A few companies made it to IPO, but the
stocks never took off. Of the companies that received a lot of public
attention, the score is as follows.
Annual Annual Yesterday P/E
High Low
Intellicorp 11 1/8 4 1/8 5 3/4 29
Teknowledge 21 5/8 8 13 1/4 loss
Symbolics 6 1/8 3 3 1/4 loss
Lisp Machines (bankrupt)
So forget an expert system startup using the venture capital route until
somebody makes it.
But venture capital is a fad-driven industry. Neural nets are hot
this month.
John Nagle
randyg@iscuva.ISCS.COM (Randy Gordon) (10/14/87)
But... That really doesn't reflect on AI's success. There have been quite a number of wildly sucessful AI projects that I know of, but they are usually buried deep in companies that do other things, and noone talks about them, so they won't lose competitive advantage. None of the pure AI companies really had a chance. All they sold were tools to solve problems, and consulting services. But one tool generates many end products, and theres only so much training you can do before your customer knows as much as you do. Companies that sell end products that use AI techniques(such as Syntelligence, or the thousand and one genetic engineering companies) are doing quite well. So are the ones that use AI as part of a tool to increase productivity or spread expertise, like Dec. If any of those pure AI companies had ANYONE with decent marketing(not sales!) experience, they would have started generating applications, (with tools as a sideline). Theres a HUGE vein of expertise out there to be mined. Many industries lack the will, expertise, or political situation to make use of the knowledge that exists and the AI techniques necessary to utilize it. AI techniques can fulfill needs that are difficult to answer with other technologies. In combination with more ordinary programming techniques, you can provide a demonstratably superior product in many areas. But you have to be answering needs! AI companies don't have problems because they are AI, they have problems because noone in them really understands how to succeed as a business, rather than as a glorified consulting firm. Randy Gordon
sr@pyuxv.UUCP (S Radtke) (10/16/87)
In article <810@iscuva.ISCS.COM> randyg@iscuva.UUCP (Randy Gordon) writes: > >That really doesn't reflect on AI's success. There have been quite a number >of wildly sucessful AI projects that I know of, but they are usually buried >deep in companies that do other things, and noone talks about them, so >they won't lose competitive advantage. Come on, Randy, let's hear what the wildly successful AI projects were. Most success stories I've heard had to be discounted considerably. They tend to be stories about developments that are full of promise, rather than systems that pay dividends or work for a living. The reports from DEC about Xcon, for instance, did not include bottom line calculations that include system development cost retrieval and maintenance cost, though such support systems are part of the infrastructure and are hard to show as profit centers. Steve Radtke pyuxv!sr
smoliar@vaxa.isi.edu (Stephen Smoliar) (10/18/87)
In the early eighteenth century a man of intense religious fervour named Johann Ernst Elias Bessler claimed that God had revealed to him the secret of the perpetual motion machine. He would tour villages in the costume of a magician and offer demonstrations of his devices. Ultimately, he attracted the attention of Count Karl von Hessen-Cassel, who undertook to serve as a sponsor. At Hessen-Cassel's expense, Bessler built one of these machines based on a wheel which was twelve feet in diameter. Hessen-Cassel then invited many of the leading scientific minds of his time to evaluate the project. In the course of this evaluation, the machine apparently ran without stopping for 54 days. Ultimately, Bessler was exposed as a fraud; and several scientific reputations were destroyed as a consequence. While the historical record of this affair is fragmented, there are several rather interesting points which I would claim are at least remotely related to the current discussion about similar sponsorship of artificial intelligence. 1. The evaluating scientists were not allowed to inspect the inner workings of Bessler's machine. Bessler claimed they would be blinded by the divine revelation (or words to that effect). Hessen-Cassel apparently did see the inner workings and was not blinded. Nevertheless, the evaluating committee agreed to accept this constraint. 2. For all the time that Hessen-Cassel possessed this machine, he never tried to do anything practical with it. Bessler's previous demonstrations with smaller-scale machines always climaxed with the machine being used to lift some impressive weight. While Hessen-Cassel was in possession of a potentially significant labor-saving device, he seemed content to keep it locked in a room of his castle. 3. Bessler was never exposed on the grounds of any scientific argument. Willem Jakob Gravesande published a "proof" of why the machine worked, and the flaw in this proof was subsequently published by Jacque de Crousaz. However, Bessler was undone when a servant girl confessed that she was powering the machine from an adjoining room. This was later discovered to be a false testimony, but Bessler was distraught by the affair. Before anyone had a chance to inspect its interior, he destroyed the machine. I do not intend to imply that artificial intelligence is like perpetual motion, at least to the extent that it is a theoretical impossibility. However, I am struck by certain behavioral parallels between past and present. My personal opinion is that Bessler was probably an extremely skilled "hacker" (in mechanics) for his time, with his personal confidence reinforced by his religious convictions. He probably pulled off a pretty good piece of work even if his mind was entirely "in the bits" (so to speak) and largely ignorant of prevailing theory. What is pathetic, however, is that those who were asked to evaluate him were willing to play the game by his own rules. Indeed, there is some indication that their opinions may have been slanted by the promise of sharing in the monetary gain which Bessler's invention might yield. Also, there is this depressing observation that the evaluation never involved putting the machine to work; they were content to just let it run on in a locked chamber. Current "success stories" about artificial intelligence are not quite as contrived as that of Bessler's machine running in a locked room for 54 days; but they come closer than I would feel is comfortable. To a great extent, the "field testing" of "applied" expert systems often takes place in rather constrained circumstances. A less polite way of putting this might be to say that the definition of "success" is in danger of being modified POST HOC to accommodate the capabilities of the system being evaluated. Thus, I feel that all reports of such stories should be viewed with appropriate scientific scepticism. On the other hand, there is a positive side of this historical retrospective. Had Hessen-Cassel actually put Bessler's machine to work, it might have been of considerable benefit to him . . . even if it did not run forever. In other words, a machine capable of dissipating its energy slowly enough to run for a very long time, while not being a true perpetual motion machine, would still be a useful tool. By concentrating on a theoretical goal, rather than a practical one, Hessen-Cassel lost an opportunity to exploit a potentially valuable resource. Similarly, sponsorship of artificial intelligence should probably pay more heed to advancement along specific pragmatic fronts and less to whether or not machines which exhibit that behavior deserve to be called "intelligent." If we recognize what we have for what it is, we may get more out of it than we might think. ACKNOWLEDGEMENT: I would like to thank Jim Engelhardt for the extensive research he has performed regarding the story of Bessler. He is in the process of incorporating his research into a play which he is calling THE PERPETUAL MOTION MAN. His research has been quite thorough, and his insights are noteworthy.