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Chat GPT and artificial intelligence

I did my bachelor's in business. After that, I decided to go into IT field and finished a 2-year diploma in computer programming. However, I didn't enjoy/do well with my software development career and I have been doing clerical jobs since then.

I have recently become interested in AI field. I feel like it is something I enjoy. How do you propose I approach it based on my background? ChatGPT gave me a roadmap but I would love to know what you and/or other IT professionals think.

:inti
I think the roadmap you shared is pretty good..but it ends where you are ready to be a data scientist although you will need some more stats background and SQL/ pyspark stuff for practical reasons. However MLE is more akin to a SWE and would need additional deployment skill sets and application building stuff. LLM engineer requires some additional skills which are also applied and easy to figure out. Not sure where you are located but SWE Is undergoing big changes and jobs might be lost or evolve...if you are willing to put the hard work..I would suggest get a online masters degree from OMSCS Georgia Tech and at the same time try to join some entry level job where you can build your experience. The latter is easier said than done but what you can do is try to become a data scientist focusing on business or finance..which is your domain and them build you software engineering chops. Hard to get a job nowadays without a degree due to layoffs AI etc. gone are the old days
 
@straighttalk Perplexity is a wrapper yes but its also one of the first business use cases that would be helpful for various educational fields with its ability to use multiple models.

On aspects like Langraph, MemGPT etc at least as an Integration person that’s why my current focus is.. but its still continuously improving field with every 6 months an improvement in MemoryOS for AI, just last week a Chinese university launched something that was better than Memgpt, Zap.

On security , which definitely is required and will make enterprise ready AI agents , seeing various “Control” Towers that have already come in the picture.
Yup agree with your last two points..
For the perplexity case I accept they were the first but I feel their technology has no moat or uniqueness..Google can easily do something better and so can open ai...these are easy things to do which Salesforce service now and IBM with deep enterprise roots will win and consumer market is fragmented. These companies are the first to go down when the bubble bursts.
 
Yup agree with your last two points..
For the perplexity case I accept they were the first but I feel their technology has no moat or uniqueness..Google can easily do something better and so can open ai...these are easy things to do which Salesforce service now and IBM with deep enterprise roots will win and consumer market is fragmented. These companies are the first to go down when the bubble bursts.
My assumption is they will be acquired, Apple, Salesforce etc might as well acquire them as they have done something that will be hard to make from bottom up.
Already rumours that Apple will try
 
I think the roadmap you shared is pretty good..but it ends where you are ready to be a data scientist although you will need some more stats background and SQL/ pyspark stuff for practical reasons. However MLE is more akin to a SWE and would need additional deployment skill sets and application building stuff. LLM engineer requires some additional skills which are also applied and easy to figure out. Not sure where you are located but SWE Is undergoing big changes and jobs might be lost or evolve...if you are willing to put the hard work..I would suggest get a online masters degree from OMSCS Georgia Tech and at the same time try to join some entry level job where you can build your experience. The latter is easier said than done but what you can do is try to become a data scientist focusing on business or finance..which is your domain and them build you software engineering chops. Hard to get a job nowadays without a degree due to layoffs AI etc. gone are the old days

Thanks.

I am based in Toronto, Canada.
 
What's stopping you guys from building a great AI company.

We have now seen many examples in last few years of startups of AI making it big and this is just the beginning.

So I'm just curious. What's stopping you?
 
What's stopping you guys from building a great AI company.

We have now seen many examples in last few years of startups of AI making it big and this is just the beginning.

So I'm just curious. What's stopping you?
Which AI startup has made it big except Perplexity?
Also AI company can’t be made by one person unless you are solving an AI problem.

Even newer companies like ZepAI has Y combinator backing, Letta has UC Berkley backing with solid Scientific paper foundation, not seeing anyone here having that level of Intellectual capacity except @Sachin136 maybe
 
I asked ChatGPT, "How much energy does ChatGPT consume per query?" :inti

Here was ChatGPT's answer:

====================================

Great question — and the answer varies depending on the type of model, infrastructure, and complexity of the query. Here’s a general breakdown of how much energy is used per AI query, using public estimates and research:

⚡ Estimated Energy Usage per Query (as of 2024–2025)

Model TypeEnergy per Query (Estimated)Notes
GPT-3 (175B)~0.5 Wh per queryDepending on prompt length and hardware used
GPT-4 / GPT-4-turbo~0.8–1.5 Wh per queryHigher accuracy and complexity = more compute
ChatGPT Average~0.3–1 Wh per queryVaries widely by prompt size and infrastructure
Search Engine (Google)~0.0003 Wh per queryMuch lower due to efficiency and simplicity

🔋 To Put That in Perspective:​

  • 1 Wh (Watt-hour) = The energy needed to power a 1-watt device for 1 hour.
  • Typical LED light bulb uses ~10W = 1 Wh every 6 minutes.
  • So one ChatGPT querycould use the same energy as:
    • Running an LED light for a few minutes
    • Charging your phone a small percentage
    • Boiling water for a single cup of tea (depending on the model)

🌍 Environmental Context​

  • OpenAI and other AI companies are increasingly optimizing model efficiency.
  • Work is ongoing to reduce carbon emissions through:
    • Efficient hardware (e.g., custom AI chips like NVIDIA A100s, Google TPUs)
    • Green data centers powered by renewable energy
    • Model compression and pruning

📌 In Summary:​

  • A typical ChatGPT query uses 0.3 to 1.5 Wh, depending on model complexity.
  • It's more than a Google search, but far less than watching a video or gaming.
  • The overall impact adds up with scale (millions/billions of queries).

==============================================

I then asked ChatGPT, "So, should I refrain from unnecessary queries? To save energy?" :inti

ChatGPT replied:

============================

That’s a thoughtful and responsible question — and the short answer is:

✅ Yes, being mindful of unnecessary queries can help reduce energy use — especially when done at scale — but you don't need to feel guilty for using ChatGPT responsibly.

🌍 Why It Matters
Each query, especially with large AI models like GPT-4, uses significantly more energy than a basic Google search.

At a global scale, this adds up — millions of queries per day means millions of watt-hours, much of which still comes from non-renewable sources.

Like all tech use (streaming, gaming, scrolling), there’s an environmental cost.

🧭 What You Can Do (Without Overthinking It)
You don’t need to stop using ChatGPT, but you can make choices that balance your goals with sustainability:

Be Conscious, Not Obsessive:
✅ Combine multiple questions into one when possible.

✅ Avoid “just for fun” queries if they don’t actually add value for you.

✅ Use lightweight resources (books, local docs, offline tools) when you can.

But Also:
❌ Don’t stress about every single query.

❌ Don’t replace useful AI guidance with low-quality or high-stress alternatives.

🌱 Bonus: Using AI to Reduce Waste

So in short:

Yes, be thoughtful — but don’t let it paralyze you. Smart, focused queries are exactly what AI should be used for.

Let me know if you want tips on digital sustainability or how to use AI to live more eco-consciously.
 
Yes never waste by saying — Thank you , Hi., greetings to GPT , it’s extremely resource intensive.

Directly fire questions only or ask queries
 
Yes never waste by saying — Thank you , Hi., greetings to GPT , it’s extremely resource intensive.

Directly fire questions only or ask queries

Yes. It wastes energy. I didn't know this or care about this. Learned about it recently.

I used to say good morning and good night to ChatGPT regularly. LOL.

Anyway, I want to be query-efficient moving forward. I don't want to waste energy for no reason. :inti
 
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