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Data Alchemy

Public • 21k • Free

8 contributions to Data Alchemy
feeling exited to be a member of data alchemy
There are a lot of basics that has to be learn' t by each one of us not by being too busy but to also stick around and work together because we would not know what can happen at any time we can even turn out to be an organisation someday and i also make a toast to the founder of data alchemy for bringing everyone together this far 💯💯💯.
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New comment Mar 28
2 likes • Mar 28
Welcome to the community
Open Source Initiative (OSI) working group is in the process of defining AI Requirements for Open Source
Founded in 1998, the Open Source Initiative (OSI) is a not-for-profit organization that defends the open source term. It is currently working on updating its definition to include open source AI. Open source generally means the software’s source code is available to everyone in the public domain to use, modify, and distribute. The real issue at hand here is the DATA that systems are being trained on. Most systems are not being transparent about it and not making their training data and methods available. https://www.euronews.com/next/2024/03/28/sorry-elon-grok-is-not-open-source-ai-heres-why-according-to-the-creator-of-the-definition
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New comment Mar 28
4 likes • Mar 28
interesting view and this will be an area of discussion for years to come, together with data privacy.
Some concerns
As an AI enthusiast that I am, some weeks ago I went to a talk about AI and its degree of intelligence and state of art, and since then I would like to share some concerns the conference left me with. The speaker was an AI specialist with around 40 years of experience on the field, so I'd trust him. One of the things that the speaker said was that the need of electricity AIs need is growing at huge rates and that is an environmental problem as solar, wind and other sources of green energy are not enough to power the growing amount of usage of AI. The other thing he said is that AI is not that intelligent yet and behind the curtain there are sweatshops and slave labour labelling data to allow AIs to perform. Speaking of concerns, he said that based on the actual power AIs have and their predictable development, future dystopian robots like terminator or robocop are ages away -if there will ever be- and that a rise-of-the-robots dystopian future is also out of reality. But about the first two, they are serious on my point of view and we should take into account and search for solutions to avoid building progress on oppression of the poor and the need, again. Have you ever thought about that? Does it concern you? Is there anybody aware of this and working on solutions?
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New comment Mar 28
3 likes • Mar 27
As any new technology, there will be challenges along the way. Those will need to be discussed and regulated. Is the same case we are now having with all electric vehicles, same challenges...where do you get the energy to charge all the grid, how do you dispose used batteries, labor conditions in the mining of lithium etc.
2 likes • Mar 27
Not saying AI is new, as you mentioned above your specialist has 40 years experience in the field, but you get what I mean.
New to Data Alchemy
It's my first year in college. I'm majoring in electronics but wanted to diversify and explore. Found out about this community through youtube and thought I should give this a try. Don't really have any prior knowledge other than python. Excited to grow each day :)
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New comment Mar 31
1 like • Mar 26
You are definitely in the right place to start learning python. This community is very helpful. Good luck!
Advice on future proof AI skills / areas
Hi all, I was hoping some may be able to share some advice. I have bought myself 8 months of time to focus on studies / upskilling myself and I hope to build some future proof employment skills - are there any general areas I could look to educate myself in, in the AI space? I do have experience in the accounting sector and I've recently been exploring data analytics, which excites me more than the traditional accounting stuff. Thanks in advance and any input would be appreciated!
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New comment Mar 28
4 likes • Mar 26
@Justin Fraenkel I agree with @Marcio Pacheco. The content from the classroom is a very solid foundation and roadmap: - Step 1: Set up work environment - Step 2: Learn Python and the fundamental libraries - Step 3: Learn Git and GitHub basics - Step 4: Work on projects and build a portfolio - Step 5: Pick your specialization and share your knowledge - Step 6: Continue to learn and upskill accordingly - Step 7: Monetize your skills (job, freelance, product) And additionally, you can look at online courses @Dave Ebbelaar referenced in his youtube channel. https://www.coursera.org/specializations/machine-learning-introduction#courses Once you have a general understanding of all AI related areas, really think on Step 5. This is probably one of the Dave's recommendations that most resonate with me, don't try to learn it all (Pick a focus area, specialize, share your knowledge). This community has proven to be very open and resourceful, so you are in the right place to begin your journey!
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Andy Oak
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35points to level up
@andy-oak-7804
Finance professional with 20 years of experience in Financial Planning and Analysis for big corporations.

Active 190d ago
Joined Mar 6, 2024
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