vatican_banker
Joined 10 years ago
Joined 10 years ago
I was in your situation in 2023 and decided to quit without a job lined up. I rested for 2 months and then, out of nowhere, I had energy and motivation to start exercising again and start working on my mental health (with the help of a therapist/professional coach). I would recommend to have one single expectation if you decide to quit: rest.
All in all, quitting the toxic workplace and taking time off was the best thing I’ve ever done.
It took me 7 months to get an offer, 9 to actually start working.
Be prepared to be out of work for ~1 year.
Because data must be on-prem, banks are stuck in legacy infra paradigms. The whole org suffers, innovation is stiffled, yada yada…
An on-prem cloud product (hardware+software) is a game changer for these companies, IMO.
My question to oxide: how easy is to integrate external hardware into the cloud? For example: bunch of GPUs or a bunch of next-gen hardware like SambaNova.
I’d be really good to allow more than two models and change dynamically based on multiple constraints like latency, reasoning complexity, costs, etc.
The answer is here. This is a cost-saving tool.
All companies and their moms want to be in the GenAI game but have strict budgets. Tools like this help to keep GenAI projects within budget.
A few questions I jotted down while watching the video on Struct's landing page:
1. the concept of channels seems to be important on Struct as channels are the starting point of threads/feeds. Could you clarify the concept of channels on Struct? Is it just a concept to group users? Can you also chat on channels?
2. Conceptually how do you handle the fact that only the threads on the realtime feed are visible to the user? Maybe there's a low-signal high-activity thread that takes space and hides the high-signal low-activity thread which results in users missing important information or reminders.
3. Tags are crucial for filtering threads, is there a way to "police" the tags? Using tags usually grow into a mess of similar-but-not-the-same collection of text. Think of JIRA tags.
4. How to handle threads created independently by different users but discussing the same topic?
5. Not a question, but I'd be interested in knowing more about private conversations between two parties. It's mentioned only briefly in the video.
Hopefully these questions don't come out as overly critical. The tool definitely has potential.
With that out of the way, basic linear algebra operations that require sophisticated algorithms and are not "embarrassingly parallel": matrix multiplication, matrix inversion, matrix decomposition (SVM, QR, etc). Some of these algos fall into BLAS and others in LAPACK.
It's the exact opposite, most numerical linear algebra is _not_ embarrassingly parallel and requires quite an effort to code properly.
That is why BLAS/LAPACK is popular and there are few competing implementations.
This man needs to learn to edit himself.
The article also mentions that the kid didn't have the symptoms or physical manifestations of spina bifida, complicating the diagnosis.
This case reads as a genuinely difficult case to diagnose.
Top talent from, say, Vietnam already speaks good English and many would jump to the opportunity to work in Japan under these conditions.
What kind of problems do mean? Environmental? Or health-related problems?
1. SEON: https://seon.io/
2.IPQS: https://www.ipqualityscore.com/
The author explains that happiness is subjective:
> The behavioral science literature often refers to happiness as subjective well-being because the meaning of happiness varies in different contexts
...and then proceeds to delineate how psychology defines happiness:
1. a person’s own assessment of their satisfaction with life;
2. how much positive emotion [...] they experience;
3. and how little negative emotion [...] they experience
So yeah, self-rating is an important factor to measuring happiness.
What is great is that you can define DSPy signature of the type “question, data -> answer” where “data” is a pandas dataframe, then DSPy prompts the llm to answer the question using the data and python code. Extremely powerful.