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And then, when you actually meet those BA retards, all they have are some Excel sheets with product codes, a few numbers associated with them, and then, they click macros for future expectations. In other words, many of these jobs are easily automatable but hidden because they sit on a person's PC and don't train others on how to use it. And then at meetings, they don't share how the metrics are derived.
They hand the hard part off to someone smarter, though after they have shat on it and made a complete nonsensical mess out of it.
In my field of research "machine learning" is the new buzzword. I have not yet seen any significant discoveries with people applying "machine learning" to difficult research problems.
We used it a lot in trading. It's just statistics w a lot of computer muscle. So what? It's just a damn technique. It still requires a genius to direct that technique towards a genius end. Otherwise it's just nonsense data.
It's just a damn technique.
We used it a lot in trading. It's just statistics w a lot of computer muscle. So what? It's just a damn technique. It still requires a genius to direct that technique towards a genius end. Otherwise it's just nonsense data.
It works for close analogies, which a chemistry grad student can predict without a computer. So far nothing new has been discovered despite massive posturing.
The Gut is missing. The Gut is life's second brain.
I modeled a Computer with a gut, bacteria, gases, acids and alkaloids all making reactions that sensors react to to stimulate AI responses.
A programmable gut that could be programmed to sense when something isn't right and create an upset stomach, or even butter flies when something exciting is about to happen.
These sensors could be triggered before other telemetry or optical sensors can even have to sense or react. Or react on stimuli those sensors may have missed.
My code is all gone, but if they ever get the web server back up
No backup on a home computer???
rd6B saysIt works for close analogies, which a chemistry grad student can predict without a computer. So far nothing new has been discovered despite massive posturing.
For our hedge fund work, a lot of that was based upon control theory, a pre-existing discipline, before ML became popular.
The difference is that ML is attempting to develop a type of control algo, without the modelling aspects, which while it may seem innovative, doesn't change the fact that it's only trying to do what engineers have been doing for decades.
Oh gosh remember when Nano-Technology was the buzzword?
Fuzzy Logic
Oh gosh remember when Nano-Technology was the buzzword?
Tenpoundbass saysThe Gut is missing. The Gut is life's second brain.
I used a mini machine learning tool called cell analysis to do most of my risk management reports as a trader. It was limited to Csv file uploads so small data sets compared to ML but I was able to find far more relevant relationships.
I have not yet seen any significant discoveries with people applying "machine learning" to difficult research problems.
The reason it's all over-blown is AI doesn't have the concept of intuition/imagination.
Checkout Phred:
https://cs.stanford.edu/people/eroberts/courses/soco/projects/2000-01/computers-and-the-hgp/phred.html
It's behind nearly every genetic discovery over the past 25 years. It's still being used in illumina's NGS machines which don't use gels.
Now that we have high quality genetics data I think the next decade will reach new heights with polygenic risk scores:
https://www.genome.gov/Health/Genomics-and-Medicine/Polygenic-risk-scores
Not all are ML or AI but many are. Also, these methods don't work out the underlying fundamental molecular biology but they are getting better and better with predictions all the time.
Being a chemist maybe you have an opinion of protein folding prediction tools that are out there these days?
Phreds looks like a statistical data analysis program, but I may be wrong about it.
Protein folding is way out of my field. It seems that there are way too many variables for this to be easily solvable.
I've reversed my stand on being able to be a'learnin' RepCons anything.
Phreds looks like a statistical data analysis program, but I may be wrong about it.
Protein folding is way out of my field. It seems that there are way too many variables for this to be easily solvable.
More importantly, how can AI improve sex robots?
https://patrick.net/post/1327438/2019-09-23-the-rin-yang-2030-initiative-fire-80-of-white-collar-workers
I was upbeat about ML/AL.
I've reversed my position on Machine Learning/AI and its influence on our current business environment.
Originally, I was under the impression that intelligent ppl were in charge of implementing ML to solving real business problems and delivering results for their shareholders and C-level suites.
Over time, I've realized that these were not intellectuals but MBA-ologists, useless shitheads who use terms like synergy, value-added, etc, without understanding what those things really mean. What's happening is that a lot of corporations are throwing cash at ML/AI, because of the fear of missing out (FOMO) against their competitors.
In other words, they don't have real business cases to solve. Ones which could make 'em money.
So in the past 6 months, I've been to conferences around the country and I've seen countless MBA-ologists, talk about ML/AI and getting customer support centers, etc, to be automated and up to snuff. I asked myself (and a handful of them) ... 'Aren't those some $16-$23/hr jobs?' I mean most companies can afford to keep lowly paid staff. What about those so-called senior business analysts (BA), living in corporate silos, earning $35-$60/hr, doing dubious work like 'revenue recognition', 'forensic analytics', and other activities with hokey metrics?
And then, when you actually meet those BA retards, all they have are some Excel sheets with product codes, a few numbers associated with them, and then, they click macros for future expectations. In other words, many of these jobs are easily automatable but hidden because they sit on a person's PC and don't train others on how to use it. And then at meetings, they don't share how the metrics are derived.
With the above in mind, as a gestalt, I predict an "AI winter" will come 2022 or at latest 2024. When companies follow the herd and toss money at 'Bridge to Nowhere' projects, eventually, a crash ensues shortly afterwards.
The only person who's using ML/AI to produce real results (which are product enhancing), is Matt McMullen of RealDoll who's making his Harmony product a chatbot which can really interact with a horny guy. I predict great things for sex dolls but not for corporate America.