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supersoldierboy94 OP t1_j7ef7rn wrote

Reply to comment by danjlwex in [D] Yann Lecun seems to be very petty against ChatGPT by supersoldierboy94

> some bad experiences thst led to these feelings

I work as an Applied Researcher so I do both research and engineering. No beef on it. It's bad to say it as beef. It's like "dev-QA" relationship. Researchers would want the largest models possible yielding the best metrics, Engineers want the easiest to deploy and monitor. The former also undermines what engineers do as just packaging it up. Yann just said it above.

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danjlwex t1_j7ejdhf wrote

I have no clue why your are being down voted.

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supersoldierboy94 OP t1_j7ejgh8 wrote

Lecun's fanbois for sure.

Or either side of the research or engineering perspective that has no clue what the other side does.

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danjlwex t1_j7ejxtd wrote

You have a lot of angst to work through, my friend. Really, you have built up some divide between research and engineering that simply does not exist.

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supersoldierboy94 OP t1_j7elvss wrote

The beef does not exist. But the divide between research and engineering exist. It's one of the fundamental reasons why some startups fail -- they dont know how to balance which and do not know how to construct a team. There's a "divide" between data science and data engineering and folks who work on that know that there is.

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danjlwex t1_j7empve wrote

In my 35 years of working with both engineers, corporate researchers and academics, I have not experienced this divide you describe. Research isn't something that happens at startups. There is no revenue to support research in a startup. The entire focus is on product.

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supersoldierboy94 OP t1_j7enajd wrote

> research isnt something that happens at startups

Entirely depends on the startup and the product. R&D happens on many startups. Unless someone has a limited exposure on AI and ML-oriented startups, this is far from truth. OpenAI is an applied research company. They produce research papers and puts it into production. In the electronics department, OnePlus has risen as a great R&D startup capable of producing rapid R&D-based products. Grammarly puts a ton of money on its R&D to create a more domain-specific GPT model because it is vital to their product.

> The divide you describe

One does not need to probe deeper into this. Ask an experienced Data Engineer, a Data Scientist, and a DevOps. There is a clear DISTINCTION of what they do and how they balance each other. The divide isnt hostile. It's more of "we want this, you cant have all of this type of relationship, besides the usual difference of who works with what.

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etesian_dusk t1_j7gp3f0 wrote

>Lecun's fanbois for sure.

The fact that you have an unpopular, and in my opinion shallow, view of current NLP, isn't an argument for calling everyone else 'fanboys'

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