The other part wonders if this is the next clinkle.
MJ has shipped stuff before though so I’m optimistic.
166 karma · joined August 7, 2011
The other part wonders if this is the next clinkle.
MJ has shipped stuff before though so I’m optimistic.
We're on a mission to simplify and optimize healthcare for humanity. Most of healthcare is digitized, but it hasn't really changed. Humans still toil away at mundane, administrative tasks. Therefore, we're turning manual work queues into fully automated workflows. We integrate into the EHR systems (something we've grown to be quite good at) using technologies across the spectrum (LLMs, OCR, Basic Models, and of course good 'ol logic).
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TL;DR - Occupational Burnout is a result of the body's inability to respond to cortisol (stress hormone) in the work environment. Sleep, vacationing & working out are a prerequisite, but insufficient to correct. The article instead recommends that people should address major contributing factors that show up most commonly:
1. workload
2. autonomy
3. fairness
4. reward: comp + recognition
5. workplace community
6. purpose: values + meaning
^ In my case, I took a hard look at each one and have been making sure I focus on addressing those that seem to be most demotivating to me. Creating a physical work environment and reading about the behavioral science of habbit forming has also been great support.
Best of luck in getting through it. You're not alone!
Also, I'm a Co-Founder here at SendHub. So if you have any questions on getting this to work please drop us a line. (ryan@sendhub.com)
There are elements of past AI models in the HTM model, however to reduce HTM's or any deep learning algorithm to a mere combination of past AI concepts overlooks the power of the right model when it is achieved. It would be like saying that Facebook is just a news feed. Sure, that's what gets most of the eyeballs, but there's a lot more there which would drastically reduce its value if not present.
What I think is most interesting is that we may find that Humans learn pretty inefficiently from the perspective of the amount of input data required over time. This may seem silly at first, but when you consider how many neurons cover the surface area of our ears and eyes and then consider the fact that it takes anywhere from 12 to 14 months for a child to speak its first word, you might start to agree with this line of thought. Also, when I consider the fact that this processing all happens in parallel even further pushes me in this direction.
Whatever the case may be, HTMs are definitely a cool area of research. For those who are interested, you should definitely check out more of Jeff Hawkins work at Numenta. They've been able to demonstrate some pretty novel things. He wrote a book back in 2006 that blew my mind. Went into deeper explanation about how HTMs could model everything from deep learning, to consciousness, creativity, and bunch of other things.
1. The config was overly complex and not flexible enough for our needs.
2. It added extra, and unnecessary deploy steps which slowed down our deployments.
3. Configuring GZIP on S3 and Cloudfront is prohibitively complex.
CloudFlare on the other hand, solves many of these problems for us.