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sarabande
Joined 452 karma
- I really appreciated this blog post, John, to know that you're doing what I've been doing without a guilty conscience.
I'm a VP eng/research at a startup and also feel like one of the few people apart from the founders who can push major technical initiatives by just doing it themselves, due to: business context, technical chops, architectural judgment, grit, and seniority to pull in cross-functional stakeholders to help out.
However, I have often questioned if it is correct that so few people in the org can do this and if I shouldn't be enabling others to do it themselves instead.
How have you been able to navigate not having any direct reports? Who does your engineering org report to and how are you able to manage conflict between org builders and your technical vision?
- I enjoyed this piece, including references to the Stoics and Spinoza. It preaches serenity, goodwill, composure, etc.
As someone in their 30s with children, work and a generally busy life, I wonder if anyone can recommend some pieces with more direct application - that is, in this vein, but perhaps an operational / how-to guide. Sometimes, it's hard to translate principles to action.
- Consider outbound AI calls as a weapon against inefficiency. What is the game-theoretic equilibrium when faced with adversaries like call centers & other businesses with labrynthian customer service?
I bet it leads to more efficiency for everyone. When inbound robocalls deluge a business, the business pushes to cost-optimize its own service.
Business replaces humans with similar AI solutions to handle the phone modality, but hopefully then reverts to great service via email/API to reduce costs further.
Then, humans using AI voice services can "de-escalate" and revert to email/API AI, e.g. going from:
1. Business: AI (Voice) or Human | Customer: Human
2. Business: AI (Voice) or Human | Customer: AI (Voice)
3. Business: AI (voice) | Customer: AI (Voice)
4. Business: AI (Text) | Customer: AI (Text)
- 4 points
- 1 point
- I like the article's premise. I would like some argument for why we'd suddenly get better at measuring something that has escaped us for at least 80 years when knowledge work became more common.
> My suspicion is that [...] there will be a surge in our capacity to measure and evaluate real-life work performance.
- It's your personal preference to be addressed with _Sie_, but languages change and German is seeing shift to the use of _Du_ even for transactional business [1]. Target audience, region, familiarity etc. will all affect which word is used. Claiming the use of _Du_ in customer relationships as "wholly inappropriate" again is an expression of personal preference, not fact.
[1] https://www.abendblatt.de/wirtschaft/article233949947/firmen...
- I also didn't know, some Googling led to this being the likely reference: https://en.m.wikipedia.org/wiki/OneWeb#2022_Russia_controver...
- Here is a summary, part ChatGPT and part me:
The “Lone Banana Problem” describes subtle biases of Large Language Models (LLMs) in AI: LLMs reproduce the statistical average of the inputs that they have consumed in the context of the question they have been asked. It's called that problem because the model used to generate images has never seen an individual banana, so when prompted always generates two bananas.
- I'm trying to use this on a 3M mp3 file to test ASR with language code deu, CPU only, and I keep getting this error -- are there limits to the MMS inference?
File "fairseq/data/data_utils_fast.pyx", line 30, in fairseq.data.data_utils_fast.batch_by_size_vec assert max_tokens <= 0 or np.max(num_tokens_vec) <= max_tokens, ( AssertionError: Sentences lengths should not exceed max_tokens=4000000 Traceback (most recent call last): File "/home/xxx/fairseq/examples/mms/asr/infer/mms_infer.py", line 52, in <module> process(args) File "/home/xxx/fairseq/examples/mms/asr/infer/mms_infer.py", line 44, in process - 1 point
- 2 points
I do wonder if it is possible to agree on a general definition of the CTO from the perspective of the job to be done, rather than how they do it.
For example, we could say the job of the CTO is to ensure the company remains technically competitive. If they do it by means of building an organization then so be it. If they rather do it by writing code themselves, then why not?