January 19, 2022
-
4
minute read

Pranay Patil: Organization as Key to Startup Success

People

For this week’s fireside chat, we sat down with one of our Forward Deployed Engineers, Pranay Patil. Pranay graduated from the University of California, Berkeley in 2017 with his BS in Electrical Engineering and Computer Sciences. He previously worked as a software engineer at Petuum and Tamr, two startups out of labs at CMU and MIT, respectively.  

We were lucky enough to bring Pranay on board in July 2021, and he’s been helping to push the company forward ever since. 

What made you interested in machine learning/artificial intelligence?

“Machine learning is where everything is headed in the future - every single thing is using, or will be using, different machine learning algorithms.

If we offload all our decision making to black box models that we don’t understand, it could have a lot of bad - even disastrous - unintended consequences. Given this, how do we make sure our models are secure and don't make any mistakes?

These are the types of issues that made me interested in this space, and Robust Intelligence in particular.”

What past life/hobby/school/work experiences do you think impacted your journey to machine learning? How did your background prepare you for working at Robust Intelligence?

“When I was younger, I read a lot of science fiction books - like the Foundation series by Isaac Asimov. Novels like those are full of crazy worlds where things go wrong, like robots and machines taking over, et cetera. They may just be stories, but these books started to get me thinking about the direction of change in the tech world generally. I’ve always been interested in this issue of protecting against unforeseen consequences. 

“Later on, in college, the whole hype around machine learning was becoming very strong. They started introducing a lot of classes on the subject when I was at Berkeley, and many of the classes I was working on were in that space. As I was graduating, those classes were getting the most interest.

“I took an AI class in college where we were covering this topic called ‘reinforcement learning,’ where you have a goal and you try to incentivize the system to go about things as fast as possible.

“If you set a goal, the algorithm could make a bunch of decisions to make a goal, but if you’re not careful about how you set a goal, it can lead to negative unintended consequences.”

What’s a day in the life as a Forward Deployed Engineer for Robust Intelligence look like?

“Basically, it’s split. Part of my day is spent talking to customers and helping them install and use RIME on their local systems, and helping them better use RIME for their own unique workflows. When I’m not on any customer calls, it’s thinking about and implementing ways to improve the customer workflow, et cetera. Generally, my job description is: finding ways to make RIME easier and more intuitive to use. Anything that can accomplish that, I’m probably working on.

I enjoy talking to people a lot, so it’s been nice to speak with a bunch of new people almost everyday, and to work on my skills talking about technical topics to people who don't have that background and translate that language.”

Why did you decide to join Robust Intelligence? What brought you to the job?

“The mission aligned with where I was at. I talked to a lot of the people during the interview process, and found that I really enjoyed hearing their perspectives. 

One thing I learned from past jobs is that while it’s great to have a lot of smart people, you have to understand what the organization is - otherwise, you’ll just default to the path of least resistance.

“Everyone here is really smart, but also understands how to organize things effectively, and is very aware of how important organization is. It’s a small company and a great environment, and I think we can really push the company to where it needs to be.
“Especially at a small startup, it’s important to have an efficient way of structuring processes. I’ve been at companies where we had a great mission, but the system was so disorganized that when we tried to work towards our goal, it didn’t get better in any way.

Robust Intelligence isn’t like that. It’s a combination of mission statement and action - which is why we’ve already had so much success and momentum.”

What would you say to anyone interested in working at RI, based on your experiences so far? How does RI compare to other startups you’ve worked at?

“First of all, if you come to Robust Intelligence, you’re going to have a great time!

“Concretely, working at Robust Intelligence offers a lot of opportunities to make a big impact - no matter your role. It’s still a pretty small company, so you’re going to be doing a lot of different types of things, and you're going to shape a lot of processes that would already be set if you joined a large company.

“In the last few weeks alone, I’ve been working on release project automation - which would have already existed if I’d joined a bigger tech company. Working here, you kinda do a lot of things and figure out what the problem is so you can fix it.

“At a company this size, you have a lot of input in the direction of the company, and you have the ability to shape and change it. 

“You get to learn a lot of new things, which is an incredibly exciting environment. You also know every person at the company - which makes it a fun place to hang out! We get dinner and lunch together almost every day.”

January 19, 2022
-
4
minute read

Pranay Patil: Organization as Key to Startup Success

People

For this week’s fireside chat, we sat down with one of our Forward Deployed Engineers, Pranay Patil. Pranay graduated from the University of California, Berkeley in 2017 with his BS in Electrical Engineering and Computer Sciences. He previously worked as a software engineer at Petuum and Tamr, two startups out of labs at CMU and MIT, respectively.  

We were lucky enough to bring Pranay on board in July 2021, and he’s been helping to push the company forward ever since. 

What made you interested in machine learning/artificial intelligence?

“Machine learning is where everything is headed in the future - every single thing is using, or will be using, different machine learning algorithms.

If we offload all our decision making to black box models that we don’t understand, it could have a lot of bad - even disastrous - unintended consequences. Given this, how do we make sure our models are secure and don't make any mistakes?

These are the types of issues that made me interested in this space, and Robust Intelligence in particular.”

What past life/hobby/school/work experiences do you think impacted your journey to machine learning? How did your background prepare you for working at Robust Intelligence?

“When I was younger, I read a lot of science fiction books - like the Foundation series by Isaac Asimov. Novels like those are full of crazy worlds where things go wrong, like robots and machines taking over, et cetera. They may just be stories, but these books started to get me thinking about the direction of change in the tech world generally. I’ve always been interested in this issue of protecting against unforeseen consequences. 

“Later on, in college, the whole hype around machine learning was becoming very strong. They started introducing a lot of classes on the subject when I was at Berkeley, and many of the classes I was working on were in that space. As I was graduating, those classes were getting the most interest.

“I took an AI class in college where we were covering this topic called ‘reinforcement learning,’ where you have a goal and you try to incentivize the system to go about things as fast as possible.

“If you set a goal, the algorithm could make a bunch of decisions to make a goal, but if you’re not careful about how you set a goal, it can lead to negative unintended consequences.”

What’s a day in the life as a Forward Deployed Engineer for Robust Intelligence look like?

“Basically, it’s split. Part of my day is spent talking to customers and helping them install and use RIME on their local systems, and helping them better use RIME for their own unique workflows. When I’m not on any customer calls, it’s thinking about and implementing ways to improve the customer workflow, et cetera. Generally, my job description is: finding ways to make RIME easier and more intuitive to use. Anything that can accomplish that, I’m probably working on.

I enjoy talking to people a lot, so it’s been nice to speak with a bunch of new people almost everyday, and to work on my skills talking about technical topics to people who don't have that background and translate that language.”

Why did you decide to join Robust Intelligence? What brought you to the job?

“The mission aligned with where I was at. I talked to a lot of the people during the interview process, and found that I really enjoyed hearing their perspectives. 

One thing I learned from past jobs is that while it’s great to have a lot of smart people, you have to understand what the organization is - otherwise, you’ll just default to the path of least resistance.

“Everyone here is really smart, but also understands how to organize things effectively, and is very aware of how important organization is. It’s a small company and a great environment, and I think we can really push the company to where it needs to be.
“Especially at a small startup, it’s important to have an efficient way of structuring processes. I’ve been at companies where we had a great mission, but the system was so disorganized that when we tried to work towards our goal, it didn’t get better in any way.

Robust Intelligence isn’t like that. It’s a combination of mission statement and action - which is why we’ve already had so much success and momentum.”

What would you say to anyone interested in working at RI, based on your experiences so far? How does RI compare to other startups you’ve worked at?

“First of all, if you come to Robust Intelligence, you’re going to have a great time!

“Concretely, working at Robust Intelligence offers a lot of opportunities to make a big impact - no matter your role. It’s still a pretty small company, so you’re going to be doing a lot of different types of things, and you're going to shape a lot of processes that would already be set if you joined a large company.

“In the last few weeks alone, I’ve been working on release project automation - which would have already existed if I’d joined a bigger tech company. Working here, you kinda do a lot of things and figure out what the problem is so you can fix it.

“At a company this size, you have a lot of input in the direction of the company, and you have the ability to shape and change it. 

“You get to learn a lot of new things, which is an incredibly exciting environment. You also know every person at the company - which makes it a fun place to hang out! We get dinner and lunch together almost every day.”

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