Top 10 Leading Stocks in Artificial Intelligence (Six Best Artificial Intelligence Tools Every Chief

1. Artificial intelligence computing power

Click on the "blue font" above and select "set as star" for the key message. Delivery time is D1!

2. Artificial intelligence software chat GPT

In the artificial intelligence revolution of software engineering, many companies are not willing to fall behind. The six best artificial intelligence tools provided to chief technical officers will put them at the forefront of industry competition. This article introduces the "best in class" artificial intelligence tools in each field of software delivery, and the six best artificial intelligence tools that every chief technical officer needs to understand.

3. Artificial intelligence AI

Audio: progress bar 00:0006:14 Back 15 seconds and fast forward 15 seconds AI is everywhere now. Its powerful functions fascinate people, and sometimes make people worry that teams that do not use AI technology may lag behind people as chief technology officer (or project leader). Part of its work is to guide people to use safe and influential AI tools.

4. Artificial Intelligence Medical

This article will select the "best in class" tools for each field of software delivery, or at least the artificial intelligence tools currently built for them that can have an impact. It is not an exaggeration to say that the "revolution" brought by artificial intelligence for software development will bring revolution to various industry fields.

5. Artificial intelligence and intelligent manufacturing

Artificial intelligence is revolutionizing software engineering, and various machine learning algorithms and AI based tools and technologies are constantly emerging, which can help developers improve workflow and improve efficiency. From developing more accurate test cases to creating more efficient code, artificial intelligence can have true practical applications in a wide range of tasks.

6. Artificial Intelligence Big Model

Developers can use tools that support artificial intelligence to automate many tasks involved in software engineering, freeing up more time to focus on core development tasks. Artificial intelligence based software testing is another exciting field of development. With the help of neural networks, developers can test their code more thoroughly and identify potential vulnerabilities and errors before they become major problems.

7. Artificial Intelligence GPT

This is also a shortcut to improve the developer experience. Artificial intelligence engineering enables enterprise teams to do more things they truly enjoy during the development process. Due to the powerful power of artificial intelligence and deep learning, the future of software development looks brighter than ever before. With the help of these technologies, developers can simplify their workflow and improve the quality of their code, And maintain a leading position with minimal human intervention.

8. Ranking of artificial intelligence leading stocks

(1) GitHub Copilot X: The future AI pairing programmer is undoubtedly the most famous and hyped AI tool on this list. GitHub Copilot X has not yet been released and may become the most popular AI tool in software engineering when it is launched.

9. Artificial Intelligence Big Data

People may be familiar with GitHub Copilot and its features, such as Copilot chat, while X is a more intelligent successor based on GPT-4. It is positioned as a user's AI pairing programmer, integrated into most parts of the engineer workflow. Here are some things it should be able to do:.

10. Artificial Intelligence PPT

Explaining code snippets, fixing errors, generating unit tests, writing pull request templates, writing CLI commands, when it is released, will simplify most aspects of software delivery - directly handling any part of the code's lifecycle. (2) Sourcegraph Cody: Using artificial intelligence to write code faster.

Can't wait for the launch of Copilot X? You can try using Sourcegraph Cody, which can help users read, write, and understand code faster. It is said to be 10 times faster. Sourcegraph Cody can read and understand users' entire code library, including code diagrams and enterprise documents, and can answer questions about it.

It is still in the testing stage (like many artificial intelligence tools nowadays) and may not always be able to do things well, but it is clearly the preferred product of the Sourcegraph team, which stated that its results are getting better every day or trying to adopt: Mutable.ai - Mutable.ai is another option.

Can do automated completion, write code blocks, and quickly drive development, but currently cannot do testing. Codium specializes in testing writing. (3) Readable: No more comments need to be written. People need clear and consistent documentation. Readable AI can automatically generate source code comments.

Poor (or missing) documentation can be a challenge faced by software engineers, especially for those who are new to code libraries or teams, and it wastes a lot of time. Readable AI can significantly reduce developers' time writing comments, allowing them to focus on more complex tasks and improve overall productivity.

Readable AI and development teams are already compatible with IDEs such as VSCode, Visual Studio, IntelliJ, and PyCharm, and can read most languages (4) Adrenaline AI: Understanding code is a daily reality for most engineering teams to spend a lot of time researching Stack Overflow.

What if a software engineer could ask an expert who fully understands the code base and immediately get an answer? This is what Adrenaline AI does. It can explain how functions work, locate the implementation location, or guide them through debugging. It is built using static analysis, vector search, and high-level programming language models.

(5) Grit. io: Automated technology debt management. What if code migration could be automated? What if artificial intelligence can handle dependency upgrades? Grit.io is an automated technical debt management tool designed to easily accomplish this task. It can automatically generate pull requests for processing details by following best practices, and it has a continuous radar to detect regression.

Developers claim that migration can be completed at 10 times the speed. If only half of this sentence becomes reality (this has not been confirmed), it will not consume a lot of time and resources to deal with these technical debts (6) Codeball AI: is the enhanced code review process tired of spending a lot of time reviewing pull requests? Codeball AI can solve this problem.

This AI driven code review tool can evaluate pull requests, highlight risks, and even approve low-risk pull requests based on the enterprise's configuration. Ultimately, it should mean that enterprises can release products faster and more confidently. It is very suitable for discovering risky code changes, and has been trained in millions of code contributions.

After training with millions of code contributions, Codeball AI can identify risky code changes and provide actionable, team specific insights. It is used in conjunction with GitHub Actions and supports over 20 programming languages. Artificial intelligence is changing the rules of the game, and this is just an attempt for the future.

Artificial intelligence in software engineering will play an important role, and keeping up with this change is a crucial success or failure for many technical teams and even the businesses they belong to. If done correctly, it is possible to find many practical potential uses of artificial intelligence, truly turning "10 times faster" from dreams to reality. Therefore, enterprises should not miss the latest developments in artificial intelligence that are changing software engineering.

Copyright statement: This article is compiled by Enterprise D1Net. When reprinted, the source should be indicated at the beginning of the article as Enterprise D1Net. If the source is not indicated, Enterprise D1Net reserves the right to pursue legal responsibility. The cover image is from Zhaotu Network (source: Enterprise D1Net) about Enterprise D1net (www.d1net. com).

The domestic mainstream to B IT portal operates the largest domestic CIO expert database of Party A and the intelligence output and social platform - Xinzhongzhi (www.cioall. com), and operates 19 IT industry official account at the same time (you can pay attention to it by searching D1net on WeChat). If you work in a certain field of enterprise IT, network, and communication industries and want to share your views, you are welcome to contribute to D1Net.

Submission email: editor@d1net.com Cooperation phone number: 010-58221588 (Beijing company) 021-51701588 (Shanghai company) Cooperation email: Sales@d1net.com Xinzhongzhi, a subsidiary of Enterprise Network D1net, is the expert database and intelligence output and resource sharing platform for CIOs (chief information officer). It has more than 50000 CIO experts and is currently the largest CIO social platform.

Xinzhongzhi provides practical services such as consulting, training, and demand matching for digital upgrading and transformation through the integration of CIOs. It is also the earliest ToB sharing economy platform in China and provides services such as headhunting, selection reviews, and IT department performance promotion. Scan the "QR code" to view more details