Research as an Avenue for Curiosity | Abby Graese | TEDxUCCS

Summary

The speaker passionately discusses research as a means to satisfy curiosity and drive innovation across various fields. They share their personal experience in machine learning and computer vision, emphasizing the importance of perseverance, continuous learning, and collaboration. The summary highlights the challenges of imperfect experiments and the excitement of discovery, as well as the competitive yet supportive nature of the research community.

Takeaways

• 🔍 Research as Curiosity: The speaker emphasizes research as an avenue for curiosity, highlighting its role in pursuing new ideas and implementations across various fields.
• 📚 Traditional Research: Described as gathering data and information on a topic with an established knowledge base, akin to researching for a trip or a historical paper.
• 🛠 Active Research: The speaker differentiates between traditional and active research, where the latter involves taking curiosity into action to contribute to a field, such as machine learning or computer vision.
• 🧠 Machine Learning Context: Provides context on working with deep neural networks to teach computers image classification, illustrating the practical application of research in computer science.
• 💡 Finding Passion: The script shares a personal journey of discovering passion in research, where the speaker was inspired by a professor and immersed in meaningful work.
• 🤔 Embracing Challenges: Discusses the inherent difficulty and imperfection in research, acknowledging that not all experiments or ideas will be successful.
• 📈 Learning from Failure: Highlights the importance of learning from unsuccessful projects, using the gaps between expectations and outcomes to fuel further questions and exploration.
• 🤝 Collaborative Spirit: Despite competition, the research community is portrayed as collaborative, with researchers eager to discuss and learn from each other's work.
• 🧐 Humility and Learning: The speaker adopts a humble approach, assuming the role of the 'dumbest person in the room' to learn from others and ask intelligent questions.
• 📈 Growth and Comfort: Reflects on personal growth in understanding the fundamentals and vocabulary of the field, and becoming less intimidated by complex aspects like mathematical theories.
• 🌟 The 70/30 Rule: Coined by the speaker, this rule represents the balance between the struggle (70%) and the exhilaration of success (30%) in the research process.

Q & A

What is the initial kind of research most people think about?

The initial kind of research most people think about is gathering data and finding information on a topic with a solid knowledge base, such as researching a hotel for a trip or historical information for a paper.

What is the second type of research mentioned in the script?

The second type of research is an active task that involves pursuing new implementations and ideas to further the fields one is working in, such as in biology, communications, psychology, and computer science.

What is the context behind the speaker's work in machine learning and computer vision?

The speaker works with deep neural networks, a form of machine learning, to teach computers to classify images accurately, like identifying a picture of a cat as a cat and not something else.

How did the speaker's professor play a role in their research journey?

The speaker's professor saw potential in them and provided the opportunity to work in a lab, which allowed the speaker to discover their passion for research.

What does the speaker mean by 'assuming that I'm the dumbest person in the room'?

The speaker means that they approach their work with humility, always learning from others, and using their curiosity to drive their research and understanding of the field.

How does the speaker describe their experience with the vocabulary in their field?

The speaker initially stumbled over the vocabulary but has become more comfortable with it over time, although they acknowledge that there is always more to learn.

What does the speaker find beautiful about the field of research?

The speaker finds it beautiful that there is always more research being done, more papers to read, and new ideas and avenues to pursue, which keeps the field exciting and ever-evolving.

How does the speaker view the imperfections in their experiments?

The speaker views imperfections as learning opportunities, stating that they always learn something from so-called failures, and these gaps often provide the basis for asking new questions and pushing the field forward.

What is the '70/30 split' the speaker jokes about with their friends?

The '70/30 split' refers to the speaker spending 70% of their time struggling with challenges and trying to understand their work, while the 30% of success and breakthroughs is what motivates them to keep going.

How does the speaker describe the competitive nature of the research field?

The speaker describes the field as inherently competitive, with labs constantly striving for the next big idea or improvement, but also emphasizes that beneath the competition, researchers are collaborative and curious individuals.

What is the speaker's motivation for pursuing research?

The speaker's motivation for pursuing research is the active pursuit of knowledge, the desire to discover new things that did not exist before, and the opportunity to push the boundaries of what was previously thought possible.

Outlines

00:00

🔍 The Essence of Research and Personal Growth

The speaker begins by distinguishing between common research activities and a more active, curiosity-driven approach to research. They share their personal journey in a machine learning and computer vision lab, emphasizing the importance of pursuing new ideas and implementations. The narrative highlights the passion and dedication required in research, as well as the collaborative and competitive nature of the field. The speaker also discusses the challenges of imperfect experiments and the learning opportunities that arise from failures, framing these setbacks as necessary steps in the pursuit of knowledge and innovation.

05:00

🚀 The Drive Behind Research and the Power of Success

In this paragraph, the speaker delves into the motivation behind research, describing it as an active task of discovering new knowledge. They reflect on the competitive yet collaborative environment of research fields, where labs compete for breakthroughs while also fostering a community of inquiry and discussion. The speaker conveys the human aspect of research, portraying researchers as individuals driven by curiosity and the desire to expand the boundaries of understanding. They conclude with a personal anecdote about the balance between the frustrations of research and the exhilarating moments of success, which ultimately fuels their passion for the field.

Keywords

💡Research

Research, in the context of the video, is presented as both a means of gathering established information and as an active task of pursuing new ideas and implementations. It is central to the video's theme of curiosity and innovation. The script describes research as something one does when preparing for a trip or writing a paper, but also as a pursuit in fields like computer science where new knowledge is created.

💡Curiosity

Curiosity is highlighted as the driving force behind research. It is the innate desire to learn and explore that leads individuals to delve deeper into their fields of interest. In the script, the speaker's passion for research is ignited by curiosity, which leads to a deeper engagement with machine learning and computer vision.

💡Data Gathering

Data gathering refers to the process of collecting information or data relevant to a particular topic or research question. It is a fundamental aspect of research and is exemplified in the script when discussing the initial type of research one might conduct, such as finding information on a hotel or historical figures.

💡Machine Learning

Machine learning is a subset of artificial intelligence that allows computers to learn from data and improve from experience without being explicitly programmed. In the video, the speaker's research in machine learning involves working with deep neural networks to enable computers to classify images, such as distinguishing a cat from other objects.

💡Computer Vision

Computer vision is a field that enables computers to interpret and understand visual information from the world, such as images and videos. The script mentions the speaker's work in computer vision, where they use machine learning to teach computers to recognize objects in pictures, like identifying a cat.

💡Deep Neural Networks

Deep neural networks are a class of machine learning algorithms modeled loosely after the human brain that are designed to recognize patterns. They are central to the speaker's research, where they are used to enable computers to classify images accurately.

💡Innovation

Innovation is the process of translating an idea or invention into a good or service that creates value or for which customers will pay. The video emphasizes the pursuit of innovation in research, as researchers aim to push boundaries and contribute to their fields in meaningful ways.

💡Competition

Competition in the video refers to the rivalry among researchers or labs to achieve breakthroughs in their fields. It is portrayed as a driving factor for improvement and collaboration, despite the challenges it presents.

💡Collaboration

Collaboration is the process of working together to achieve a common goal. The script discusses how, despite competition, researchers are willing to facilitate discussions and share knowledge, which is essential for collective progress.

💡Failure

Failure, in the context of the video, is an inevitable part of the research process. It is presented not as a setback but as a learning opportunity, providing insights that can lead to new questions and directions for research.

💡Success

Success in the video is described as the rewarding outcome of research efforts, such as when experiments yield positive results. It is the fulfillment of the research process that motivates the speaker and other researchers to continue despite the challenges.

Highlights

Research is an avenue for curiosity, with different types including gathering data on established topics and pursuing new ideas in various fields.

Day-to-day research involves finding information for practical purposes like travel or academic research papers.

Active research involves pursuing new implementations and ideas to advance fields like biology, communications, psychology, and computer science.

The speaker's passion for research was ignited by working in a lab on machine learning and computer vision for over a year.

Machine learning involves teaching computers to classify images accurately using deep neural networks.

Research provides the opportunity to contribute to growing and relevant fields in today's society.

The speaker found their passion for research when they started working on ideas outside of formal lab hours.

Working with intelligent people helps the speaker understand the theory and impact of their research.

Assuming the role of the 'dumbest person in the room' encourages asking more intelligent questions and learning from others.

There is always more research to be done, with new papers and ideas constantly emerging.

Research is inherently difficult, with no perfect experiments and many ideas not working out as expected.

Learning from failures is a crucial part of the research process, as gaps between expectations and outcomes drive further questions.

The speaker jokes about a 70/30 split between struggling with challenges and experiencing moments of success.

The 30% of success keeps researchers motivated through the 70% of difficulties and challenges.

The field of research is competitive, with labs vying for breakthroughs and novel ideas.

Despite competition, researchers collaborate and facilitate discussions, interested in each other's work.

Research is driven by curiosity and the desire to push the boundaries of what was previously thought possible.

Transcripts

research as an avenue for curiosity

before we get started I just wanted to

get a couple of definitions out of the

way because there are different types so

the first kind of research is probably

the research that we all think about

initially it's gathering data finding

information on a topic that has a solid

knowledge base behind it so this is the

kind of research that we would do if you

were going on a trip

so finding information on a hotel or

museums that you could go to while

you're there there's also this is also

the same type of research that you would

do if you were doing a research paper on

a historical figure like Thomas Edison

you'd take the time to go check out a

book look at some information on the web

find all of that information so this is

what a lot of us do on a day to day

basis but what I want to look at is

different so I want to look at research

is an active task its pursuing new

implementations and ideas to further the

fields you're working in so this is

taking your curiosity and putting it

into action so this can happen in a lot

of different fields from biology and

communications to psychology and

computer science and this is the kind of

research that I love so I in addition to

being a student here I've had the

opportunity for the past year and a half

to work in a lab doing research in

machine learning and computer vision and

to give a little bit of context behind

what that is we work with deep neural

networks of form of machine learning to

teach a computer that when we show it a

picture of a cat it should classify it

as a cat and not as a dog or a boat or

anything in between so in a broader

context however I have the opportunity

to do meaningful work in and contribute

to one of the most relevant and growing

fields and in today's society in the

past year and a half after one of my

professors saw something in me that I

never would have seen in myself I've had

the opportunity to find my passion I

kind of knew it was my passion when I

started going home and thinking and

eating dinner and 20 minutes later I'd

pull up my laptop and start working

again because I would find a new idea or

something else that I wanted to work on

because if my experiments not running

it's broken and there's something I can

do to fix it

or if I have an idea to how better get

information out of that experiment I'm

running so I have the opportunity to

work with people who are extraordinarily

intelligent every day they help me to

understand the theory behind what we're

working on and the big picture impact

that we our work is going to have so I

always take the stance of assuming that

I'm the dumbest person in the room but

I'm learning to ask more intelligent

questions and using my curiosity to

drive what we are doing and how to

better use that in to in furthering the

field so I definitely know more than I

did a year ago I'm more comfortable with

the fundamentals

I no longer stumble over the vocabulary

that I read every day and I'm less

intimidated not completely not

intimidated but less intimidated by the

mathematically intensive parts of the

papers that I read but the beautiful

thing about it is there's always more

research being done so there's always

more papers to read more vocab to

stumble over my favorite and there's

always new ideas and avenues to pursue

because of this so the difficult part

about this is that it's hard you are

never going to have a perfect experiment

you're never going to have an idea

you're always going to have an idea or a

project that doesn't work out like you

hoped it to I just got finished working

on a project a couple months ago where

I'd spent three months trying to get it

to work and we were like I guess it

doesn't work at all so let's move on to

the next one so we do get to learn from

this information though we always are

going to learn something from these

so-called failures and it's often these

gaps between the expectations and the

actual outcomes of what we're learning

that provide us with the anomalies in

order to ask another question to push

the fuels further shift directions and

continue to work I have a joke with a

lot of my friends that it's a 70/30

split so we spend 70% of our time

banging our heads against

the wall and trying to understand the

theory behind what we're doing it trying

to understand why it's not working

but it's that 30% that keeps us going

through that so it's the 30% of crazy

success where your experiments are

running you're getting information out

of the out of your experiments the

results are good and it's just that

feeling where you get that in the pit of

your stomach because it's working you're

getting what you want

so this 30% is what keeps me going

through the 70% especially when I pair

it with the motivation behind what we're

doing so the pursuance of research is

the pursuance of knowledge is an active

task so you're finding out new things

and new things that didn't exist before

so we it the field itself is inherently

competitive all of the labs are always

vying for that next accuracy jump or the

next novel idea that's going to change

the field and that's a that's an

opportunity so we get to use these and

force collaboration between them as well

because all of the authors are always

willing to answer your questions they're

always willing to facilitate discussions

and they're always interested about your

work as well because something that you

say may be the anomaly or the spark that

hits in their brain that leads them to a

new idea so underneath all of the

competition we are just people who are

really curious about what we're working

on and we want to do more and want to

know more in order to push the

boundaries of what we previously thought

was possible thank you