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We will benefit from Artificial General Intelligence within 10 years! - DSBoost #25
🎙️ Podcast of the week
Given the rapid progress in artificial intelligence, I believe there's a strong chance I'll witness and benefit from artificial general intelligence during my lifetime, potentially within the next decade.
The data industry is rapidly evolving, with frequent introductions of new models and tools. To remain relevant, data professionals must prioritize continuous learning and adaptability.
“Eating your own dog food” is crucial! - use your own products to ensure they meet expectations and work effectively.
The open-source community is rapidly evolving, with new models being introduced regularly and standardized benchmarks to assess their quality.
Muglia emphasizes the importance of exploring and experimenting with AI technology to modernize organizations.
🧵 Featured threads
🤖 What happened this week?
The web is full of chattering bots, but which is the most useful and for what? A comparison of Bard, Bing, and ChatGPT.
Wix already has several AI generation options for site creation, but now, it’s betting on algorithms over templates to build a custom site for you.
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💬 Interview of the week
This week we interviewed Siddhesh Bangar, who is a Computer Science grad. Enjoy:
What did you study/are you studying (if your background is different from DS, how did you end up in the field)?
I’m a Computer Science grad from Vidyalankar Institute of Technology in Mumbai, India. Guess what? I’m super stoked because I’ll be heading to Trinity College in Dublin to pursue my masters in data science!
I’m a total data science junkie and have been diving into this field for about a year now. It all started with a random Coursera course on data analytics that I didn’t even plan on finishing. But boy, was I in for a surprise! As time went on, my interest in data science grew like crazy, and I ended up exploring other exciting domains too.
What are your favorite resource sites and books (ML/AI)?
First off, we’ve got YouTube, the ultimate goldmine. It’s like a treasure trove of data science, machine learning, and AI courses. You can find so much amazing stuff there, especially for beginners. Just pick a channel or playlist, dive in, and with practice every day, you’ll see yourself improving like crazy.
The next best option I swear is the official documentation itself. Some of them are super well-maintained, making it a breeze to learn and understand.
And let me tell you about Twitter too! I've started learning from some amazing creators and teachers there, like David Andres, Levi, Akshay, Sasi, and many others. They're rocking it in their respective fields and post some seriously informative content for us data science enthusiasts. I myself share my learnings there as well. It's like a whole new way of learning.
What got you into your current role (portfolio, certification, etc.)?
Let me tell you how I ended up in this awesome AI Researcher role at MIDAS Lab in Indraprastha Institute of Technology, Delhi.
I basically dove headfirst into the world of AI, data science, and machine learning on my own. I devoured a ton of articles, research papers, and online resources and took a few courses on Coursera and Udemy to further sharpen my skills. Having a few cool projects under my belt really boosted my resume as a third-year engineering student.
One of my classmates decided to send out cold emails to multiple university labs in search of an internship. Guess what? He actually landed an offer! Seeing my impressive portfolio and resume, he was kind enough to refer me as well, which ultimately helped me secure the offer too.
[Note: The power of network + portfolio]
What do you enjoy the most in your work?
I absolutely adore learning and getting into some math from time to time. I'm happy that my job lets me do both! I'm constantly diving into research work, devouring all those fancy technical papers and articles.
It's like a never-ending journey of discovery, and I couldn't be happier about it!
Also, I really enjoy teaching and sharing what I've learned on Twitter or other platforms.
What tools do you use the most / favorite tools?
There are a few developer tools that I absolutely love, and among them, the greatest of all time is definitely VS Code. It just nails every little detail perfectly.
When it comes to reading research papers, I rely on Drawboard PDF. It's great for going through those papers and extracting the information I need.
When I need to create intricate and detailed diagrams, Draw.io is my go-to tool. It helps me bring my ideas to life in a visually appealing way.
Do you use ChatGPT or other Al tools during your work? If so, how do they help you? Do they change your approach to problems?
We've got this open source code of language models that we work with, and they give us a hard time sometimes! It's like an error party when we try running them on our local devices or SSH server. But, when we bring in ChatGPT or other AI pals, things start to change!
Instead of spending weeks pulling our hair out to debug those nasty errors, we can now crack the code in just 1-2 days or even an hour! It's like having a super-smart assistant by our side, helping us hunt down those bugs and saving us from going crazy.
So yeah, we're big fans of ChatGPT in our work. It's become our go-to for debugging code and doing code reviews. It's like having an AI teammate who's always ready to lend a hand.
Which one of the recent AI/ML models will have the most significant impact on the industry in your opinion?
GPT models have indeed made a massive impact on the AI market and have established their dominance. They have excelled in various applications and are widely recognized for their capabilities.
In addition to GPTs, there are other noteworthy models that show great potential to shape the industry further. Take, for example, Google's LAMA model. It's a significant contender that has the potential to gain considerable traction and make its mark in the market.
Another exciting area to explore is reinforcement learning, where models like AlphaGo and AlphaZero have achieved groundbreaking accomplishments. These models have demonstrated their ability to play complex games at superhuman levels, opening up possibilities for applications in fields like robotics, autonomous vehicles, and personalised recommendation systems.
What is the biggest mistake you've made? (preferably DS related)
One of the biggest mistakes I made during my data science learning journey was neglecting to continue practicing and coding regularly.
When the COVID-19 pandemic hit and schools and colleges closed down, I stopped actively learning and practicing coding. This hiatus caused my skills to become rusty, and when I eventually returned to the learning process, I had to start from scratch again.
It serves as a valuable lesson to continuously hone and maintain skills, even during disruptions, to avoid losing momentum and having to start over.
What is your most significant achievement? (preferably DS related)
While I haven't accomplished any major milestones thus far, this interview experience stands out as one of my most cherished achievements to date.
Additionally, when I began sharing content on Twitter, I received numerous messages and compliments for my contributions. This recognition and positive feedback were immensely gratifying, as they motivated me to enhance my skills and deliver even more valuable content to my audience. It served as a valuable opportunity for growth and allowed me to refine my abilities.
Can you share a fun fact about yourself?
While I don't have any mind-blowing fun facts to share, I must admit that I find teaching more enjoyable than learning, to be completely honest. That's precisely why I have a deep passion for creating content centred around teaching data science and machine learning.
Interacting with my audience on platforms like Twitter and LinkedIn brings me immense joy, and I'm currently focused on achieving my goals of establishing meaningful connections within these communities. It's a fulfilling journey, and I'm excited to keep making valuable contributions and expanding my network along the way.