Submitted by supersoldierboy94 t3_10uw974 in MachineLearning
danjlwex t1_j7ed72r wrote
My take is that you seem quite intent on painting him as petty. His statements seem quite reasonable and rational, especially in the face of the over exuberant reactions we mostly see about chatGPT.
> Mostly on the research side which immediately puts him very hostile against engineers... It's a classic case of a researcher-engineer beef
Seems like you have had some bad experiences that led to these feelings. There is no built in animosity between these groups. Just different goals.
fallweathercamping t1_j7edw3y wrote
This. Majority of reactions are irrationally exuberant and often pablum for the vacuous “content” creation cycle. It’s as if, if one doesn’t affirm the super positive, life altering results surely to come, you may get left behind. Let’s see what actual problems ChatGPT solves.
supersoldierboy94 OP t1_j7edvto wrote
Fair point. But you can be correct and petty at the same time. Remember that he blamed the people using Galactica casually as the reason it got paused. Then wonders and asks people why ChatGPT hasn't faced the same backlash given that "it spouts sh-t*.
Although one could argue that usable LLMs in production are quite revolutionary. NVIDIA'S GauGan or GAN based txt to image models, the base diffusion models have been there for a year or two but hasn't received the same publicity and profits as Stable Diffusion or Midjorney. It's basically the same line of framework.
It's narrow-minded thinking to brush the architecture upgrades and the engineering work that made it possible -- which has always been his statements. But that is a fair point considering he is mainly a researcher not an engineer.
supersoldierboy94 OP t1_j7ef7rn wrote
> 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.
danjlwex t1_j7ejdhf wrote
I have no clue why your are being down voted.
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.
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.
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.
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.
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.
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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