AI in the realm of Success for Startups

Unveiling how AI helps a starup grows as fast as they possibly could

kinfish

kinfish

@KinfishT

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In current situations , There is much going on about AI and it's impact and its derivative products as well. Hmm.. Personally i am satsified by what they currently provide based on my current(Dec , 2023) job occupation in some specific senarios but other than that it was not that much helpful for to progress much which any nontechnical personal could expect :) . Dont panic - only exception does(just programmer jokes) , tldr yeah let me break down my points that helped me and the vise versa

the pros i had with AI

  • It reduced me a time that i usually waste just wandering about specific thing on internet like it kind of gives you a hint staright away
  • It kind of gives you a redundant peice of code that you usually looks for in much organized form. Yeah it is just from online resources like github , gitlab , and some other codehosting platforms based on the licencing that they anotate with the projects, :) i dont , they might not keep that as well , who know that why OpenAI and Microsoft are being like 2 faces of a coin in Program Partnership , as well any data that come accros to them which seems valid might get be fed by them to explore more dots and connect them
  • It can debug a code at a high level like just scratching the surface for most kind of mid - high complex projects which is something you do with the company or startup for most of the time
  • It can help me build a esteem my confidence when i usally talk to him as a consultancy like more of the time even tho the project seems quite serious it always say 'Yeah it is possible'
  • It can also help me organizing some sort data like automatic parser based on some format which is really highly depends on your prompt . it might not go well if does not prompt well
  • It helps me also in kind of paper situations when i really have to write something that i want to speak it out loud on the paper as if i had a strong sense on each press of the words.

Huh, Let see the cons.

  • I have quite explained it on the pros part roughly but as i mentioned it does not always cope up with mid - high project which seems because of some reasons -- One thing will be since the data is trained on some specific domain that hugely depends public projects or simply codebases which poeples or organization makes it opensource because they just think that not only it is just simple codebase but to kind of attract opensource developers to work on a way complex project which seems pretty contrasting . But one thing i have noticed is like when one company outsources their codebase they have already determined the values that they would get out of it and seeing some doing same product outsourcing it , this is common on a release of somekind of SDK's for most part other than the most famous opensource opensource products like Linux , GIT , Docker , PG - Postgres which seems not enough for AI to help me even to write something of based on my current job requirements yeah based on my tasks , the domain might be a really bottle neck for it for connecting the dots -- Other thing , When working on comapnies it is different. Some of the comapnies really prohibits using Outsiders GPT's services any LLM's because they are always of afraid of that there code might be leaked as a result of debugging or something like ideation thing going on there since it really do have some kind of crazy algorithms for curated learning with having a conversation with you which is a kind of smmart duet. -- Yet another thing when it comes to creating an optimized code at fly time is so difficult for him so that entirely depending on it , your job may get you ended up with in a loop.

  • It might do something that is always have a solid codebase which you can always refers to and something standard which makes a LLM models to be so creative on that standard since there codebase does not often change like implementing some kind of backend feature like auth/oauth , Database connectivity , Standard Cron thing , Creating CRUD controllers as well grouping routes which the every backend based on , which it is quite talented at. No offence Backedn Devs :. I mean i am not offending anyone here but it is pretty solid and standard stuff i really do and other backend dev do other than some specification which really might helps us a lot but one thing we got to note that it helps a lot on backend stuff specially for Junior Backend Dev's scratching out the surface and somehow beyond that . Yeah You still have a complex stuff you really do which LLM's or any AI can not do! but for most of the case it is not the same except if you are not developing the AI itself . Bro trust me you job is so much secured. However when it comes to UI/UX and Frontend Dev there aint no standard which you got have to follow which is always a dynamic which really confuse it a lot not to build a complex UI. Like lets take our site - arezarmada.com if you asked him to do this site clone i bet you it aint do it about 10-20% of it other than pesimist codes :) Still No Offence i am not offending any of LLM's but it really do take time to do that but currently v0.dev is up for public beta for you to try on have a conversation with iterative conversation about each details which is good progress but it aint near to do a complex ui. other than that it gives you a really beatifull UI ready made by other or you can even do it from scratch And big ctx here - i am not talking about man-like-cyborg or any humaniod robots which is another level's Yeah that was my take aways on AI and it's impact for me personally but when we go deeper to group of me :) like a team mates. Nothing will change but it has some dynamics on it

  • Increased Efficiency: AI algorithms can automate repetitive and time-consuming tasks, freeing up human workers to focus on higher-level tasks that require human creativity and decision-making skills.

  • Improved Customer Service: AI and ML-powered chatbots and virtual assistants can provide 24/7 customer support, handle a high volume of inquiries and support multiple languages.

  • Enhanced Data Analysis: AI can help startups process and analyze large amounts of data much faster than humans could, leading to better decision-making and improved performance.

  • Personalization and Targeting: AI can be used to personalize products and services for individual customers, resulting in improved customer engagement and satisfaction.

  • Lower Costs: AI can reduce the costs associated with manual processes, such as data entry and customer support, as well as minimize human errors.

All those mentioned are a good aspects of AI which litrally do have a great control and tempo on context switching which i really amazed of , Let me take you back to 1 or 2 month before today , what just happend was i applied to some company in US and they sent me an invitation to schdule an interview, till we started the interview i did not even notice AI will interviewed me and i hop in there on the company internal meeting management tools and yeah since there is a naame labeled on it when i joined the meeting i never thought it would be an AI. but yeah he - the AI thing introduced him self as he being an AI and he would love to conduct an interview with me and me was what , how , whattt like it was confusing at very first glance of hearing that but yeah after that he requisted me turn on my camera and my mic which really was off .. and i was what hmm.. this dude is good at this and i setted up everything and he started asking me about my experience by parsing through my resume which i really do thing it was but the thing was different i guess they trained the AI based on github , linkedin , resume and other information i have entered there while i was applying and that is not the scariest part like while i was explaining him about my past experience and project . i was mentioning something that was not near enough to find it anything that i have provided for them but he really picks that one and asking me to explain and how i applied it with my project and he even do a summary of what would he think would be good if i used the stuff i mentioned to him on some standard way and man he really trained on my project and he was mentioning about deep integration about it and i said heck not this much not an AI but it is what it is . I Wish you could have an experience with that . there was not any tiny piece of defect on understanding each other like it really went so smooth and i probably sure there might a confusion if did that with human!. Yeah i was shoked at that time we did about 30min interview he kindly requested me last the interview and he even said he was excited meeting me becuase of something he mentioned for me that he really likes about me :) i was this was a dude. yeah there is a lot going on let's go back to our topic :)

  • Automation of Repetitive Tasks: AI and ML algorithms can automate many of the repetitive tasks that consume a significant amount of time and resources, such as data entry, customer support, and invoicing.

  • Improved Workflow Management: AI and ML can help startups streamline their workflows and processes, making it easier for employees to focus on high-value tasks and prioritize their workloads.

  • Predictive Analytics: AI and ML can be used to analyze large amounts of data and predict future trends and customer behavior, allowing startups to make informed decisions and allocate their resources more effectively.

  • Data Quality and Availability: AI and ML algorithms require large amounts of high-quality data to be effective. Ensuring that data is accurate, complete, and consistent is a critical first step in successfully adopting these technologies.

  • Technical Skills and Expertise: AI and ML technologies are complex, and organizations often struggle to find the technical skills and expertise required to implement and operate these systems. Investing in training and upskilling employees can help organizations overcome this challenge.

  • Integration with Existing Systems: AI and ML systems must be integrated with existing systems and processes in order to deliver value. Ensuring that these systems are compatible and can work together is a critical step in successful adoption.

  • Ethical and Regulatory Concerns: There are ethical and regulatory concerns associated with AI and ML, particularly with regards to data privacy and bias. Organizations must be mindful of these concerns and implement appropriate safeguards to mitigate risks.

  • Resistance to Change: Change is always difficult, and many organizations may be resistant to adopting new technologies like AI and ML. Communicating the benefits and addressing concerns is key to overcoming this challenge and driving successful adoption.

The Role of Investors in AI and ML Startups

  • Investors play a critical role in the success of AI and machine learning (ML) startups, providing the capital and support that these businesses need to grow and succeed. Here are some of the ways that investors are helping to shape the future of AI and ML startups:

  • Funding: Investors provide the financial resources that startups need to develop and bring their products and services to market. This includes funding for research and development, marketing, and other critical activities.

  • Mentorship: Investors often bring a wealth of experience and expertise to the table, and can provide valuable mentorship and guidance to startups as they navigate the challenges of starting and growing a business.

  • Networking Opportunities: Investors are often well-connected in the business community and can provide startups with valuable networking opportunities. This can help startups to build partnerships, secure customers, and raise additional funding as they grow.

  • Strategic Direction: Investors can help startups to identify and prioritize their goals, and provide guidance on the best strategies for achieving these goals. This can include advice on market positioning, product development, and more.

  • Exit Strategies: Investors are often focused on realizing a return on their investment, and can help startups to identify and pursue exit strategies that will maximize the value of the business. This can include selling the company, going public, or pursuing other exit strategies.

Yeah with out being said , Let me concluded my thought yeah AI really helps on Startup / Companies as well. Yeah it is what we are leveraging right now at ArezArmada We are hugely integrated with AI to provide a seemless experience from either side of the client - both business and technical clients throught out the entire process, which will be avalaible really soon at least for public beta. If you would love to contribute on this blog please ping me at my twitter - https://twitter.com/KinfishT Hope to see you with another blog really soon.

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