dragostudor

The site is crap, but the advice is spot on

And crypto sites seem "reliable". Doesn't matter what it "seems", but what it is. Watch the dude on youtube.

Of course. Better selection of people you invest in. Refinement and understanding of self.

Follow https://understandingrelationships.com/life-coaching-service... - read free book 10-20 times :)

Read 'No more Mr. Nice Guy'.

Invest in relationship knowledge as much as you do in other topics of interest.

That's what I observed as well. Finding that generic but valuable use-case is quite tough. Selling it is on a totally different level. The impact it can have should be well worth it though

Working on https://superhero.re/ - smarter tracking and management of equipment failures. What are you up to?

Interesting, that is my experience at Pfizer as well, where I lead projects end-to-end, from problem discovery to solution deployment and I pretty much did everything, from talking to coding

Are you working on these? Got any links?

What is stopping such projects from scaling? Are the economics not there yet?

sounds awesome, have been working on several such project as well. would be great to share experiences

If you're working on any of these, it would be great to chat

Fascinating, would be great to chat about your thoughts on the future of the space

Would love to find out more about the lessons that you've learned in the process

Fewer and fewer people are interested in manufacturing jobs, especially the less glamorous ones. Large manufacturers are having a hard time using analytics and more advanced systems because of qualified labour shortages. I've spoken to manufacturers whose technicians can't even write or follow instructions correctly. Sometimes, sending 10 technicians to inspect an asset would results in 10 different opinions about possible issues / failures. All of these could lead to lower quality product and increased unscheduled downtimes, lower revenues etc etc. But, it is definitely important to still allow people to use their brains and come up with better options

*hundred billion dollar companies with a manufacturing component :)

I've started looking into CO2e reduction techniques as well. Would be great to discuss. Working with a client in the food space who is doing this just to learn more

On-site visits, or contract work on the shop floor should be a good way in. Alternatively pro-bono work, part time or longer.

Tracking stuff is hard. I wonder why QR codes won't work in this case, or something similar, or super basic otherwise / stickers or codes at first. Might be more annoying to generate and maintain them initially. CV could work really well to keep track of inspection steps as well, or to recommend what you should do next, and how to do it

Spot on, many of these challenges are common across the board - from my father's plant to Pfizer and others I got the chance to work with. There is however a massive talent gap when it comes to high quality software / ML people in these industries as well. It's tough to get experts to generate quality data and 'recipes' for others to follow when their KPIs are not aligned. Maintenance and reliability don't seem to be sexy enough areas for management to invest in, especially if the value proposition is anecdotal at best. Would be great to chat about your approach for solving some of the above

Many companies store huge amounts of documents, but every team does it in its own way. One template can quickly result in thousands of variations. If robust documentation principles are not used from the very beginning (checklists / reduction in free text, visual indications, etc), it will be a nightmare to make sense of that data afterwards. Also, there is no value in generating large amounts of text data unless you can easily scan it and retrieve the information of interest

Definitely, transfer can only happen when knowledge is organised and understandable by a variety of stakeholders, with different backgrounds (education, languages spoken, years of expertise)

My thoughts exactly. Knowledge transfer in manufacturing / industrial environments is something that I'm working on.

- Language models / NLP applications for processing large amount of technical text data (SOP, documentation, technical data, machine text logs, voice to text, video data processing for speeding up corrective action, training, onboarding and highlighting areas of improvement / bottlenecks), digitising documents and extracting failure reasons / equipment names / spare parts / processes involved and making associations between them for pareto analysis, better search or process improvement recommendations

- Recommending the next steps to fix something / remote intervention / do something etc. Lowering the expertise threshold required for technicians, electricians, mechanics or reliability engineers to be effective.

- Enabling operators to become data scientists by enabling to train AI models via their day to day activities / analysis. Building better UX in general and providing simple tools that even a toddler could use.

- Autonomous factory use-cases / supply chain automation.

Would love to discuss with people who find these things exciting

[EU/UK/US] Building platform where hardware startups/integrators can build and scale their supply chains, on-demand, and go from prototyping to mass production in days. Looking for the crazy ones who are hungry and top of their game.

It is important to work with someone that you can trust. Someone that can push through hell together with you and not abandon everything at the smallest bump. It takes a strong character, ambition and sense of urgency. When it comes to non-technical / business people, it might be counter-intuitive, but having attended a good university or having worked for a good company can indicate high intelligence and not entrepreneurial drive. This being said, you can still collaborate with technical people that are comfortable with selling the vision, product and services, can hustle and are reliable.

Also, be careful of non-compete agreements by joining other start-ups.

There are several ways in which you can find good co-founders:

1. Don’t prioritise finding a co-founders, just start building something and reach out to people. They might love what you’re doing and come on-board.

2. Get recommendations via your network about people who want to build a company and have complementary skills / similar goals.

3. Increase your visibility, publish your thoughts, network and debate about the future - randomness / serendipity is a wondrous force

4. Accelerators such as Antler and EF - as a last resort.

I’m also looking for smart, relentless people that want to build a better future for generations to come. Don’t hesitate to reach out via linkedin - username: tudordragos

There is a difference between revenue and transactional value! In the industry it seems that the revenue rate is ~10%. We can look at HomeAway for example - acquired by Expedia in 2015, for 3.8bn, 2014 revenues were ~$446.8m (https://en.wikipedia.org/wiki/HomeAway), for about 500 - 1k employees (can't find any data on this). https://ir.expediagroup.com/?ReleaseID=880362 does not list any information on Hotels.com generated revenues. But overall, Expedia generates ~450k/employee, and I'd expect this to be the norm, maybe higher for Hotels.com, by max 50%. The writer has no business knowledge and is generally uninformed when it comes to the requirements of managing a vastly complex company. For Airbnb, maybe 20-30% of people are working in customer support from India, and get paid $5000/year. An average is not a good indicator of a company's ability to make money

Sounds interesting! could you share some metrics related to the performance of your model / explained variance / adjusted R^2? Do you have sufficient airlines who have a tendency to drop prices instead of steadily increasing them the closer you get to the desired departure date? And most importantly Did you backtest your model and run a simulation before pursuing this project to test its viability?

London | UK Looking for great people to collaborate with. Currently into nutrigenomics and healthcare. Developing a deep learning model which 99% faster, 99% cheaper and more accurate at identifying skin conditions as compared to a dermatologist. Fundamentally interested in solving big problems and building scalable businesses with people that I truly enjoy working with. Looking for researchers in bioinformatics, coders or people that can sell and also be friendly :)

Linkedin: https://www.linkedin.com/in/tudordragos/

My Background: ML/Data Science/Research + Business / Strategy