DeepMind's AlphaCode - Better Than OpenAI Codex?

DeepMind's AlphaCode - Better Than OpenAI Codex?

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Hard

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The video discusses DeepMind's AlphaCode, a model designed for competitive programming. It compares AlphaCode with OpenAI's Codex, highlighting AlphaCode's focus on novel program synthesis and human-like problem-solving. The development process involves pretraining on GitHub code and fine-tuning on competitive programming datasets. AlphaCode generates multiple solutions, filtering them through test cases and clustering algorithms. Its performance is evaluated in simulated contests, performing at a median level. The video also mentions the release of datasets for benchmarking.

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7 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary focus of DeepMind's AlphaCode model?

Developing chatbots

Creating art using AI

Solving competitive programming problems

Generating code for web development

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does AlphaCode differ from OpenAI's Codex?

AlphaCode is designed for image recognition

AlphaCode is a chatbot

AlphaCode is used for creating music

AlphaCode focuses on competitive programming

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a key component of AlphaCode's training process?

Using handwritten notes

Training on social media posts

Pretraining on public GitHub code

Using private company data

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of the clustering algorithm in AlphaCode?

To create new programming languages

To group similar solutions based on outputs

To design user interfaces

To generate random code snippets

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does AlphaCode filter potential solutions?

By using a random selection process

By choosing the most complex solution

By selecting the shortest code

By checking against example test cases

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What was the performance of AlphaCode in simulated contests?

It performed as well as the median participant

It outperformed all human participants

It was not tested in contests

It failed to solve any problems

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What resource did DeepMind release to aid in benchmarking?

A book on AI ethics

A guide to competitive programming

A dataset of competitive programming problems and solutions

A new programming language

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