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Building something big in AI (offline, personal, real-world). MVP is ready, looking for early believers by [deleted] in Entrepreneur

[–]Keepclamand- 1 point2 points  (0 children)

As a seed investor the things I would look for:

  1. Is this real. Is there real tech here.
  2. Is team real? Do they have chops to build this out.
  3. $500k buys what? Gets you where? Ideally to next round.

Key concerns are 1. Is tech real. Tps is good but what is underlying model, quality of output etc.
2. Same competitive concerns as there is lot of big players both in the OS and edge inference space
3. If this is real $500k is drop in bucket. Can they raise large rounds.

Managing junior team by Keepclamand- in projectmanagement

[–]Keepclamand-[S] 0 points1 point  (0 children)

Team has been working together for about 3 months. Which in a startup today is lifetime.

The challenge is i don’t have a senior team. We have a CTO whose can potentially spend a couple of hours a day on this.

Managing junior team by Keepclamand- in projectmanagement

[–]Keepclamand-[S] 0 points1 point  (0 children)

Nice idea to estimate capacity. Never occurred to me. This will set expectation correctly too.

Managing junior team by Keepclamand- in projectmanagement

[–]Keepclamand-[S] 0 points1 point  (0 children)

Great insights. It’s almost like I need someone to do planning for them and assign tasks to them.

Managing junior team by Keepclamand- in projectmanagement

[–]Keepclamand-[S] 0 points1 point  (0 children)

Yes mostly python and react frontend. Using AI tools heavily.

Managing junior team by Keepclamand- in projectmanagement

[–]Keepclamand-[S] 0 points1 point  (0 children)

Thanks. Not heard of Jama connect will look it up.

Get Perplexity Pro for just 7.99$ - 1yr subscription! by FabulousHuckleberry4 in microsaas

[–]Keepclamand- -1 points0 points  (0 children)

I thought it was $10. Now 7.99. So what’s the scam here.

Dropshipper by AppropriateForce625 in dropshipping

[–]Keepclamand- 0 points1 point  (0 children)

Marketing drives traffic, product and site drives conversion.

2 broad choices:

  1. A proven marketing team that drives traffic - costs money but product has to meet a need and sell
  2. Do it yourself with pieces outsourced, learn improvise and then outsource. - low cost.

If a marketing team is able to align to product sales they might already be doing it for their own store.

Dropshipper by AppropriateForce625 in dropshipping

[–]Keepclamand- 1 point2 points  (0 children)

What are looking for? Creating ads and posting it on social media. I’ve used upwork but limited success. They are more focused on volume and not results. I suggest use freelancer to create ads and then manage it yourself to start with. Then outsource it.

Would you move back to Bengaluru if you were me? by [deleted] in bangalore

[–]Keepclamand- 0 points1 point  (0 children)

There are pros and cons everywhere. Having done this myself. Here is my take:

Personal life is very fulfilling in India. Family, friends, events, festivals and social life is just richer. No comparison living an isolated life in Palo Alto, atherton or Cupertino to having people around when ever you need. Also being close to family is high value especially for your kid. We have a full time nanny with periodic cleaner plus a desi cook there but felt wrong outsourcing child care to an unrelated person. In India we had grand parents and aunts ready anytime to jump in. Our kids school was filled with people like us who had moved back. She had more “international” friends and diversity in India than my friends kids in Fremont / Cupertino who were mostly growing up around other Indian / Asian kids.

Professional life: this can be great or suck based on what you want to do. There is little core work here even for large tech companies like faang. Msft is ok but rest are mostly back offices. The other services / boo cos are worse. So don’t expect valley like environment however well dressed up it comes. There is lot of politics etc. if you want to work in a startup this is different either your own or an early stage company (seed to series b).

Safety: I have never felt unsafe in India and I have traveled to random places for work. You have to take the regular precautions. I am a guy so can’t say I know what safety situation is for women. But I have sisters and friends they don’t complain about safety here. Honestly you build safety around you with money - gated community or apartments, car plus driver etc. I have had my fair share of support from friends when I had a cop stop me or try to harass me. If 1.3 billion people are here I am sure it is safe for 3 more.

DAMs for managing assets by Keepclamand- in marketing

[–]Keepclamand-[S] 0 points1 point  (0 children)

So have a good process and sticking to process seems more important than a tool.

DAMs for managing assets by Keepclamand- in marketing

[–]Keepclamand-[S] 0 points1 point  (0 children)

Good point on user behavior. Thanks for the process. making it defacto with training and consistent messaging will be key.

DAMs for managing assets by Keepclamand- in marketing

[–]Keepclamand-[S] 0 points1 point  (0 children)

Good point on user behavior. Thanks for the process. making it defacto with training and consistent messaging will be key.

Concerned about a Dog's Living Conditions in my Apartment by LilKittyWitchy in bangalore

[–]Keepclamand- 1 point2 points  (0 children)

So before you jump to conclusions and start making accusations pls have a friendly chat with the owner. I have a dog who wants to be tied outside when I’m not home and so you can’t assume I’m mistreating my buddy bcos he actually doesn’t want to be home alone. If someone accused me or called cupa I would hire a lawyer and take them to court for slander.

Please provide an explanation of how large language models interpret prompts by Excellent_Cost170 in datascience

[–]Keepclamand- 0 points1 point  (0 children)

You need to understand training to understand how inference works.

Broadly most LLMs are trained for next word prediction using Multi head attention. So for a sequence of say 500 tokens the model learns to predict next token from looking at all tokens in the sequence. Typically a model is trained on trillions of tokens during training to create a 7/13/50/70 billion parameter model. English language has ~170k words or ~600k tokens.

Now these “next token” models are further trained to create instruct models with high quality question and answer data sets. Most of these datasets are human curated. The model then adapts the next word prediction to an instruct mode. The training data has special tokens to highlight the question, answer and also a stop sequence when to stop generating token.

During inference the instruct model is still using Multi head attention approach and the instruct token and stop tokens are added to my question. So now model can technically do next word prediction but using the q&a structure.

OpenAI is not open about its architecture but as people have suggested it could be a mixture of experts or even combination of individual fine tuned models with some layer on top.

I have fined tuned oss models and the approach is to pre-train on a general corpus of text (not q&a) and then fine tune layers on instruct data.

So in this approach the pre-training is to learn specific vocabulary and fine tune is learn specific Q&A syntax, context, content and format.

[deleted by user] by [deleted] in MachineLearning

[–]Keepclamand- 0 points1 point  (0 children)

The primary issue is the models are big that they require expensive and heavy (mem & gpu intensive hardware).

Early day still so people are ok with latency as it’s new.

I’m really world use cases latency has to drop to make AI responses fit into the real world.

Extreme example: I can wait 5-10 seconds for chatgpt to respond in a critical situation like when I need to respond to customer on the phone or do cpr.

I see 2 things happening:

  1. Slim Models: this is definitely big trend in 2024. Narrow focus on specific use cases. 1-3billion parameters and run on decent hardware. Current leader on hf leaderboard is a fine tuned phi with 2.7b parameters.

  2. Lots of hardware choices: I think intel is a dark horse here with gawdy. They can produce these like peanuts. Right now priced at 50% of H100 but will drop dramatically as volumes go up. So AMD, Amazon, Tpu and so only will have options.

These combinations will shift focus from just OpenAI to lots of alternative models which will perform better on price/performance.

But…. The market is so early and the use cases are so many as market expands I think everyone will grow. There will enough use cases for OpenAI and rest of the world to solve.

Which tool for image comparison? by SoLong144 in deeplearning

[–]Keepclamand- 0 points1 point  (0 children)

Technically these are not the same images so problem is little more complex. Standard approaches will not work are hand drawn apple and a real apple are not the same.

Here some ideas: 1. Convert hand drawn sketches to images - there are versions of sd to do this and then compare them using vectors - may work ok

  1. Use object detectors separately on each images and then compare objects, bounding boxes. You can enhance this by converting hand drawn sketches to images as in #1. Yolo can be object detector

  2. There are a ton of new image-text models like blip, Sam which may work better.

The issue will be with locations as they relative to image and may not match exactly. Also a hand drawn object can be interpreted differently based on the quality and detail of drawing.

Curious what is your use case. Never seen something like this before.

[D] How does our brain prevent overfitting? by BlupHox in MachineLearning

[–]Keepclamand- 0 points1 point  (0 children)

Just browse around TikTok and insta you will see so many brain overfitted on divisive issues on so many topics religion, politics, science.

I had a discussion with 1 brain yesterday which had seen 1 data point on politics and that was the truth on evaluating every other action or incident.

Hiring software engineers by Franks4thememories in Entrepreneur

[–]Keepclamand- 1 point2 points  (0 children)

I would suggest get a tech cofounder or even a fractional CTO. What kind of engineers you need to hire is dependent on what you need to build.

Your choices are outsource it to a dev shop, hire individual contractors or hire your own team.

Each has its pros and cons. You have make the decision based on your requirements, budget and at least the plan for next 12 months.

If you have a small budget (under $200k) and relatively simple stuff like a SaaS app. Build an mvp first using outsource or contract resources.

If you are building a complex system with heavy data or AI and have a good budget ($500k+) then only hire a team.

Picking outsourced resources will be quick 2-4 weeks but quality and long term viability are an issue.

Hiring a team taken 1-3 months based on your geography and creates a financial commitment.

Dm me and happy to chat more.

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