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73 karma · joined October 12, 2014
This discussion itself offers insight on the actual need for technical professionals to be able to logically reason through non-obvious [information] structures.
I've anecdotally suspected that the ability to synthesize information into a navigable data structure and subsequently analyze it, both from internal and external POV, is not a hard requirement for the majority SWE positions.
I'm struggling to understand why this system would be offline while the FTS website is still online: https://www.ftc.gov/
Is there a technical reason for the registry to go offline, or is it an intentional casualty of the power struggle in DC?
https://apps.apple.com/us/app/pico-ai-server-llm-vlm-mlx/id6...
Witsy:
https://github.com/nbonamy/witsy
...and you really want at least 48G RAM to run >24B models.
Considering the topic of a new photo-diode, the professor's name is perhaps unfortunate.*
As it stands, these systems have yet to make a compelling case for intelligence.
https://www.satellitetoday.com/telecom/2022/09/07/apple-to-d...
Answer: .300
In modern times, a season batting average of .300 or higher is considered to be excellent, and an average higher than .400 a nearly unachievable goal.
I just never expected this to apply on such a massive scale.
They may build it only to shut it down as the world waits decades to recover from something potentially worse than the CFC debacle.
There is value in communicating figuratively and/or with metaphors. When creatively solving problems, looking for trends or drawing a hypothesis out of the ether, it is often desirable to avoid specifics.
In my opinion, one's inability to comprehend and respond to any given statement at multiple levels limits their upward mobility.
For those of you who apparently missed the "American Politics" course in your higher education, Democrats have been better at resolving domestic challenges while Republicans have done better on international issues.
Si tacuisses, philosophus mansisses.
Most are easily intelligent enough to realize how long their odds really are. Furthermore, they have the intellect to appreciate the true effort they have to make before they reach financial payback.
Any reasonable person with the math skills to visualize risk vs. reward will usually walk away --but not the quintessential entrepreneur.
This is not a flattering trait. For this reason, it is rarely, if ever, associated with successful entrepreneurs.
“I” is a lie. There is no “I”.
The brain has two halves, right and left. The right side is spacial. The left side is lingual. Generally.
Both halves of the brain receive stimuli from our senses and build models of the environment that are optimized for their respective roles.
This gives each of us two models which we use to navigate our environment: a spacial model and a lingual model. These models each run in their own hemisphere and are very different from each other in both function and form.
The spatial model is innate. We are born with it. The lingual model, we acquire. (We must learn language before we hit puberty or we lose the capacity to do so. Search for “linguistics Genie” or “linguistics wolf boy” for details.)
Rather, this article is a commentary on the fact that practically all schools fail us.
In school, we sit in class, exposed primarily to lingual input. We consequently build an effective lingual model of explicit rules of our world. But but we are left to our own devices to build our spatial model, which we do from our own activities while following the “explicit rules” we know.
Every once in a while, we stumble upon some visual/real world representation that allows our spatial side to realize a concept that is well known to the lingual side.
A thousand years ago, even Ptolemy's geocentric model was good enough. After all, it offered an effective means for simulating and predicting planet movement and solar eclipses. But it was complex. It took men of "great learning" to understand the solar system according to Ptolemy's model --something that most current grade schoolers understand intuitively.
In all likelihood, concepts like string theory and neural networks are comparable traps for us today. This is not a pleasant thought. So we're not motivated to search for better alternatives until the current model evidences an insurmountable flaw.
I'm not saying that string theory or the neural network approach is wrong. Obviously it's not. Just remember that Ptolemy's model wasn't wrong either, at least with regard to the moon.