Calculus Made Easy is the best!
379 karma · joined February 3, 2018
When I read to learn, I take notes, I highlight, I reflect and write my thoughts on the subject.
Reading is a highly effective way to learn and absorb information, if you engage with the text, and make it an active experience, rather than a passive experience.
Reading isn’t about memorizing a few sentences. It’s about understanding a subject, the contents within, and being able to apply to various contexts you encounter throughout your life.
Whenever I encounter a problem or challenge in my personal or professional life, I can immediately recall and reference the knowledge or wisdom I’ve gained from books.
And if I can’t, I find the book I’m missing, and actively read it to assimilate a new understanding.
I was thinking, why isn’t it possible to use this technology to create levitating objects or vehicles???
Like UFO type flight.
Just attach powerful emitters around the craft.
This article makes me think this might be possible.
F= m*a
If waves possess mass, then it could be used as a means of force.
The brain is composed of two hemispheres, each with different regional faculties working together. Each region is responsible for producing different models, based on its responsibilities, sensory inputs, regulatory functions etc.
As a whole the brain is a massive neural network. But each region possess its own neural network (grid cells/columns), and I wouldn’t be surprised if there were sub-neural networks at play, some that are unique to each person, based on their neurological development, environmental conditioning, and overall personal adaptations.
It’s easy to see how these regional neural networks are responsible for specific statistical modeling, which then factor into other regional models, and so on, in order to arrive at the correct output response.
Also resonates with Gestalt theory/psychology, which makes a lot of sense from a complex systems processing perspective, I’m just not sure what current neuroscience says about it.
I think this theory is very promising for AI.
I look forward to seeing more of their applied work.
https://www.scientificamerican.com/article/no-link-found-bet...
There are currently 4 steps in the manufacturing process, with a final inspection at the end. They have about 35 production lines in total, and will likely have over 60 when they finish. New lines will have higher output.
They run two 12 hour shifts a day, 7 days a week.
The bottle neck is MRO at the moment. Material costs are a factor, but I know nothing about that.
In the space of 3 years they implemented these 35 lines. Getting them up and running to meet the demand and timelines required massive investment, and cost savings measures were sidelined.
They’re just not beginning to figure out ways to cut costs in order to achieve profitability.
I don’t know if Tesla has a contract that dictates the cell price, but I know Panasonic production is not profitable at the moment. They will be, hopefully in the upcoming years.
Their battery production is the most state of the art. Not only the battery technology, but the manufacturing process. It’s unparalleled by a long shot. The scale is breathtaking. Around 3.5 million cells a day with a target over 10 million.
From what I know, bottle necks are costs. High equipment manufacturing costs, and high maintenance costs.
Space isn’t the issue. They have plenty of space.
They have a contract with Tesla to produce for them, but Tesla’s demand is so high they can’t produce enough. Production is 24/7. Even if Panasonic wanted to they couldn’t sell to anyone else. I don’t know what kind of price negotiations they have, but current battery production is not profitable. This I know.
Also, Panasonic just partnered with Toyota to produce batteries for all their EV’s.
Additionally, the Gigafactory is just 1 battery production location. Panasonic has many. Some in the USA, and others in Asia. They sell their batteries to many companies. Just not the same ones they’re making for Tesla.
And it looks like 4,400 in the Model 3
I know the Gigafactory battery production intimately. I can tell you they don’t cost less than $2.50 per cell at the moment.
I don’t know how they are making money on this. I’m inclined to believe they’re losing money, or someone is somewhere in the line.
Maybe they expect those battery costs to decline rapidly in the near future?
What do you think?
The battery pack alone costs more than $20k.
Tesla can’t produce that car for $15k and make a profit.
Gigafactory Battery production is expected to continue ramping up, with higher throughput lines, but operating costs are still exorbitant, and battery production is barely breaking even at current production. In fact, from what I know they’re in the red.
I don’t see a $35k Model 3 until battery production costs cut in half, which I won’t expect for another 3-5 years.
I know Tesla is beginning to manufacture it’s own batteries, but to be honest, I don’t see them succeeding.
Non-competes really only matter for people with exceptional knowledge of something.
From a business standpoint, the legal resources to build a case against a single “average person” who signs a generic non-compete are not a good investment.
But like I said, it’s a judgement call. Anyone in the possession of that exceptional knowledge should be able to determine the risk.
And often when they do, they lose. But it’s a judgement call. I’d say the fear of non-competes has more power than the non-competes themselves.
2. Assume maximum responsibility for achieving this vision— expand your mind in a way that allows you to see the largest sphere of influence over your desired outcome. Often we think too small, and get stuck in the weeds. We wait for permission. Take responsibility. Act, and ask for forgiveness later. You alone are responsible for your dreams.
3. Practice daily meditative reflection— spend more time alone, in isolation, with yourself. Be still for long periods of time, let your mind open, and listen to what arrives, what presents itself to your mind. Pay attention to pain— discomforting thoughts and feelings are teachers pointing us where we need to go and what we need to do. Write down these thoughts. Write them all down. List, connect, associate, outline. Let these thoughts illustrate that vision, and materialize it with every connecting realization.
4. Spend time organizing these thoughts. Prioritize. Distinguish the signal from the noise. Always keep the goal in mind— each idea should connect and justify the goal, the vision. Each of these ideas should produce clarity. Create a plan, with goals, and steps for each goal.
5. Execute. Make the vision manifest through intentional activity. You alone are responsible. Do not depend on anyone. Learn what you need to learn. Partner with like minded people, who share similar visions.
6. Repeat this process daily.
I’d just say this: Know your customers, know the market, know their needs, know their challenges.
Ask yourself: what are you solving for?
The answer is your value proposition.
Your value proposition depends on the customer, but you should be targeting a market with similar needs.
“SPIN selling” is a good framework.
You must establish “common ground” with customers. It’s how you build rapport and show you understand their needs and demonstrate your competency and expertise.
Technical sales is all about problem solving. It’s idenitfying problems (known or unknown to your customers) and introducing solutions that add value to their organization, the product, or the person. Understanding your customer, their environment and needs, and establishing common ground is essential for identifying and introduction technical solutions.
Feel free to email if you’d like to discuss the philosophy of technical sales in more depth: tranchms@icloud.com
Two companies I work with in the Bay Area who are changing the game.
Not to mention that UX was terrible and clunky and not intuitive. It’s suppose to be easy to use, easy to program, that anyone can just role it up to an existing operators position and teach it in five minutes and you’re up and running. Wrong.
As mentioned, the only interface was the obnoxious swivel screen, and the only programming controls were... dials with a push button, one located on each arm and one on the back. Yes, you had to scroll through menus and across pages to select and modify programs in endlessly confusing menus that literally made you regret ever getting involved with the company.
Yes, it had some nice collaborative safety features built in, some patented titanium s joints that flexed for safety like tendons yet maintained nice accuracy.
But no one cares about your fancey safety features if it’s nearly impossible to use, and fails to seamlessly integrate into existing systems.
This is a classic mistake. Build something epically fancy, but totally worthless to 90% of the people that would use it, because it just doesn’t play well. Learning curve is too high. It’s not plug and play/ fails to understand industry compatibility requirements, or it’s too niche.
Because I sold these things, I quickly learned they were terrible.
However, Universal Robots were on the right track from the get go. They were coming from the industrial automation world, they understood market fit. They made a device that was easy to use, intuitive, that leveraged existing programming methods and incorporated some collaborative programming technology in tandem. Maybe their gear mechanisms weren’t as safe, but they passed all the requirements, so what did it matter in the end? Fancy safety joints were NOT the most important selling point for collaborative robots. Reducing downtime to increase output and profits is, and that means easy integration and quick programming. Not to mention UR was just a robot arm, and not this wacky monstrosity of a machine and wheeled based (which was optional for ReThink but not really). And UR was super compatible. It was basically like conventional single arm robot with servos slowed down and given fancy torque feedback algorithms and some sensors for safety and tracking.
The guys who started ReThink were out of their depth. Just some academics who had some success making commercial robots who expected an entire industry to conform to their fanciful dreams of robots with dopey emoting faces working along side their human comrads.
Just pissed money away.
And the thing is, they were one of the first, and positioned to be one of the best. Collaborative robotics is a massively growing field as humans and machines work in ever closer proximity.
But ReThink totally choked. Had the wrong design engineers, with no industry experience. They failed to understand industry needs and existing automation culture and prevailing systems infrastructure.
This company is a classic case study on how to completely botch the opportunity of a lifetime because of failing to understand existing market fit.
Can’t we combine centralization and decentralization?
Must it be all one or the other?
Birth rates may decrease, but that’s why we have immigration. Men and women both work these days, doubling the labor pool.
I don’t understand this comment.
Will they ban bagged lunches?
This is defying logic.
I want to know what restaurants are paying off what politicians.
Watch the next ban be on home kitchens- ha!
The bigger issue politicians should be addressing is an adequate housing supply.
High rent depletes any surplus income that otherwise would be spent eating out at restaurants.
https://www.youtube.com/watch?v=GBTUVg91bao
You don’t have to be a math wiz to appreciate the octonion model and it’s implications for fundamental particle physics.
It really is a beautiful insight of profound proportions.
“Red pandas were once thought to be closely related to the giant panda, but genetics has shown they are more closely allied with the raccoon and weasel families. They are secretive and gentle creatures, spending most of the day sleeping curled up with their tail wrapped around their head.”
It’s old school, and it does the basics. I recommend.