#TabNine

[safaabbas]

Building Smarter Websites: Exploring the Benefits of AI in WordPress

#WordPress #web development #plugin #SEMrush #Automattic #amazon #netflix #SEO #tabnine #Brainstorm Force

[the-cooler-sidestep]

everybody i'm sorry i'm a filthy traitor the AI got me alright

#text #tabnine is so good oh my god

[kaiasky]

im trying one of those copilot things (tabnine) for a personal project bc yknow. i guess.. i remember this reddit post about a brilliant engineer and draftswoman who couldn't learn to use a mouse and so never picked up CAD and then got let go by her company when the company went fully digital. very sad and i think about it sometimes. anyways.

the point is. im trying an ai tool. and mostly it's not that great, but. When writing documentation, its very funny to always have an autocomplete of the next word.

Because MY stupid brain will go blank and type a nonsense word, and then ITS stupid matrices will jump in with:

its perfect. its cybernetics. we are of one essence and one mind and that mind thinks thoughts like gamer API documentation

#kaia.mypost #kaia.lint

[visionarywire]

#AI #chatgpt #ChatGPT Alternatives #technology

[synthcryptid]

pet peeve: coders who use ai coding plugins like copilot and tabnine, under the belief that "it's the future of coding!", and grow incredibly defensive when their PRs get turned down for blatant license violations

to the surprise of literally no one, there is not a single ai coding plugin that uses a dataset that's actually respectful of copyleft licenses like the GPL. and because copyleft licenses are incredibly prominent among the open source community (where ai coding plugins leech from), these plugins very frequently copy and paste copyleft code verbatim, often with no attribution (something that's in direct violation of most copyleft licenses!)

we wonder if the subscription fees of these plugins is the reason why some folks are incredibly defensive when they get caught up in license violations because of them. you can do the exact same thing these plugins do, but in a way that actually respects licensing, and for free(!), by literally just browsing open source repos yourself and paying attention to their licenses. if you're working on an open source project, then these licenses are almost always straight-forward to comply with!

#bhijn posting #rambling #ai sucks #we wish all ai-peddling charlatans a very Get The Fuck Away From Open Source #op #also this is egregious with byond in particular because literally the vast majority of byond repos are AGPL. dm is not AI-safe

[deandacosta]

Tabnine https://t.co/5TUAFRzpwf

http://dlvr.it/T5h4bN

[flowres921]

The Evolution of Coding: A Journey through Manual and Automated Methods

In the ever-evolving landscape of technology, coding stands as the backbone of innovation. From its humble beginnings rooted in manual processes to the era of automation, the journey of coding has been nothing short of fascinating. In this blog, we embark on a retrospective exploration of the evolution of coding methods, tracing the transition from manual to automated approaches.

The Dawn of Manual Coding:

Before the advent of sophisticated tools and automated processes, coding was predominantly a manual endeavor. Programmers painstakingly wrote code line by line, meticulously debugging and optimizing their creations. This era witnessed the emergence of programming languages like Fortran, COBOL, and assembly language, laying the groundwork for modern computing.

Manual coding required an intricate understanding of the underlying hardware architecture and programming concepts. Developers wielded their expertise to craft intricate algorithms and applications, often pushing the boundaries of what was thought possible. However, the manual approach was labor-intensive and prone to errors, leading to the quest for more efficient methods.

The Rise of Automation:

The evolution of coding took a significant leap with the introduction of automated tools and frameworks. Languages like C, Java, and Python democratized programming, offering higher-level abstractions and built-in functionalities. Developers could now focus on solving problems rather than getting bogged down in low-level implementation details.

One of the pivotal advancements in coding automation was the rise of Integrated Development Environments (IDEs). These software suites provided a comprehensive environment for coding, debugging, and project management, streamlining the development process. IDEs like Visual Studio, Eclipse, and PyCharm became indispensable tools for developers worldwide, boosting productivity and collaboration.

Furthermore, the advent of version control systems such as Git revolutionized collaborative coding practices. Developers could now work concurrently on the same codebase, track changes, and resolve conflicts seamlessly. This fostered a culture of collaboration and accelerated the pace of software development.

The Era of AI and Machine Learning:

As technology continues to advance, coding is undergoing yet another paradigm shift with the integration of Artificial Intelligence (AI) and Machine Learning (ML). Automated code generation, predictive analytics, and intelligent debugging are becoming commonplace, augmenting the capabilities of developers.

AI-powered coding assistants, such as GitHub Copilot and TabNine, leverage vast repositories of code to provide context-aware suggestions and autocomplete functionality. These tools empower developers to write code faster and with fewer errors, unlocking new possibilities in software innovation.

Moreover, Machine Learning algorithms are being employed to automate mundane coding tasks, such as code refactoring and optimization. By analyzing patterns and best practices from existing codebases, ML models can suggest improvements and identify potential bottlenecks, saving time and effort for developers.

The evolution of coding has been a journey marked by innovation and transformation. From manual coding practices to the era of automation and AI, developers have continually adapted to embrace new technologies and methodologies. As we look towards the future, the fusion of human creativity with machine intelligence promises to redefine the boundaries of what can be achieved through coding.

#ManualCoding #AutomatedCoding #CodingComparison

[recursosformacion]

Usando la Inteligencia Artificial en la programación

Hace unos meses, me decidí a probar un poco como funcionaba eso de la inteligencia artificial en un entorno de programación, con Java, Javascript, React, Angular u otros , en una situación de desarrollo normal. Mi primera prueba fue con Tabnine, en aquel momento, me ofrecía un mes de prueba gratuito, y, aunque reconozco que me gusto, (teneis los comentarios aqui), cuando acabó el mes, pensé en…

View On WordPress

#AI #eclipse #Formacion #java #STS

[ericvanderburg]

Tabnine Chat Empowers Developers to Pick and Switch Between LLMs

http://securitytc.com/T51LY8

[aisupersmart]

Tabnine On AiSuperSmart Ai Tool Directory

#chatgpt #nightcafecreator #runwayml #sora #openai #dalle #generativeai #stablediffusion #aiart #midjourney #ai #machinelearning #videogenerator

[yesitlabs-llc]

🚀 Step into the future of coding with these 5 groundbreaking AI Coding Assistant Tools! 💻✨ From GitHub Copilot's intelligent suggestions to TabNine's deep learning-powered autocomplete, these tools are here to revolutionize your coding experience. Say goodbye to mundane tasks and hello to seamless development. Dive into the world of AI-powered coding and unleash your creativity! 🛠️🔥

#AICoding #DeveloperTools #ProductivityBoost #webdesign #developer #codeigniter #custom software development

[nenamatic]

AI is becoming more and more popular in the software development world, and we think it's for a good reason. Developers are always looking for ways to make their workflows faster, more efficient, and more user-friendly. AI has changed the game for developers, but before you think it's going to take over, remember that developers are the ones who come up with the ideas. AI can write code and suggest improvements, but it's up to you to make them happen. So let's check out the 9 best AI tools for great developers to get more job done. Claude Claude, the HTML0 version of the AI chatbot and content generator, was created by the AI startup Anthropic, which is known for creating funny content. It's been praised by users for its security and personalisation, as well as its great comedy and creative content creation. It's got a great ability to get feedback and improve its communication skills, which makes it stand out from other chatbots. Unfortunately, dangerous requests can still pass through when they're put into an imaginary scenario. Unlike other chatbots, Claude doesn't come with a free version and can't connect to the internet, and it's only available in Europe and the US. GitHub Copilot GitHub Copilot was created in collaboration with Microsoft and costs just $10 a month. It provides code suggestions based on ML algorithms and open-source code, but developers have to make sure their suggestions are accurate due to its limitations. It's available in two versions: Copilot for people and Copilot for businesses. It can turn NLP prompts into code, provide multiple-line functions, handle corporate policies, and help with corporate proxy servers. It also offers code recommendations based on styles and context, giving users the option to customize and choose. TabNine TabNine is an artificial intelligence (AI) based code completion tool developed by Codota. TabNine uses machine learning algorithms to provide smart code suggestions for over 20 programming languages and 15 editors, including popular versions like JAVA, python, C++, vscode, intellijs, and androidstudio. One of TabNine’s main strengths is its ability to learn from your code base. It analyzes patterns in your code and provides you with personalized and contextual recommendations. The dual-engine nature of TabNine (local and cloud-based) makes it stand out from the crowd and allows it to operate without an internet connection. While TabNine isn’t a complete script generator, it significantly improves the speed of writing code by speeding up the development process and preserving the code’s privacy. However, TabNine is not without flaws, it’s free and is designed for smaller projects, and it can overload the interface with irrelevant suggestions. CodeQL CodeQL is a really powerful semantic analysis tool that was built by GitHub. It's different from other code analysis tools because it doesn't rely on pattern matching. Instead, it looks at the connections between code segments, data flows, and potential vulnerabilities. It's like trying to understand the language, not just looking for keywords. Your code snapshots capture not just the code itself, but all the dependencies, connections, and the system it's part of. Think of it like creating a virtual version of your app. Usually, these tools just find isolated issues, but they don't look at the bigger picture. CodeQL looks at how different code segments interact and can help you identify complex vulnerabilities that could be across different parts or files. CodeWP Isotropic has created CodeWP, an AI-powered WordPress code generator. It's specifically designed for WordPress developers, with features like Live collaboration, real-time code feedback, and easy version control. You can use it with JavaScript as well as PHP, and it's designed with popular WordPress plugins like WooCommerce in mind. Its main advantage is that it focuses on WordPress, giving you code recommendations and taking care of all the work that goes into WordPress development.

But it can be a bit unstable at times, and it's not great for big projects. AlphaCode AlphaCode is a powerful AI tool that can create code on a huge scale and use critical thinking based on experience. It has a huge transformer-based model with 41.4 billion parameters, and it offers training in Python and C++. It's free, but you should know that the learning process is up to you and can be a bit shaky. You can train using GitHub code repositories and refine it through CodeContests with techniques like generating samples, smart filtering, and clustering. It can tackle complex problems similar to what humans do, and its ability to create code on a big scale combined with smart filtering puts it in the same league as humans. Phind Phind is a search engine that's tailored to developers. It can provide accurate and useful answers to questions about programming, which sets it apart from other AI tools like ChatGPT. Plus, if you search for related websites, Phind can give you the most complete answer to what you're looking for. If you have any coding worries, Phind can help you out by giving you clear, precise, and scalable answers that are easy to do. Plus, the results of your search give you more info than just the AI-generated one, so you can get code examples and useful info all at once. Phind is free in July 2023 and it's a great resource for developers. AskCodi AskCodi is powered by OpenAI, a software that can generate code that answers questions about programming and provides useful code ideas. You can easily install AskCodi to your preferred IDE (Visual Studio Code), PyCharm, or IntelliJ IDE. It will help you improve your code. AskCodi can create SQL queries and DocStrings as well. As one of the best things about AskCodi, it can generate codes from easy-to-understand prompts. It can answer questions about coding easily, so you can understand even the most complicated code concepts. It can suggest code as you write, which helps you avoid errors and generate efficient code. It has been designed for users who want a user-friendly experience when coding by taking care of the tedious tasks like generating code and answering questions about coding. No-cost plans are available for AskCodi; premium plans start at $7. RegExGpt Creating RegEx phrases can be a real pain, especially if you're new to the game. But don't worry, RegExGPT makes it easy! You can create simple RegEx expressions using simple English prompts. This takes the guesswork out of creating complex RegEx patterns, so developers don't have to spend hours writing and testing them. All you have to do is enter the input string and the expected output, and then you can create a RegEx pattern that matches it. It's a great tool for automating things like filtering and analyzing text. Just make sure to double-check the expressions you create before you start. Conclusion These tools aren't perfect, but they're always improving and getting better, so they're more reliable and dependable for users. Things like how much computing power you have, how you handle your personal data, how much it costs, what language it supports, and if it's available can all affect how you choose to use it for different types of development. But the good news is that these AI tools have a lot of potential. As they get better, developers will be able to streamline their workflows, get more done, and solve complex problems more quickly. It's a bright future, and it'll be fun to see how they develop over the next few years. Also, you can read y other articles- Top 21 ChatGpt Plugins You Should Know Who Created ChatGpt? Who Is Happy To Owns It Now?

#ARTIFICIALINTELLIGENCE #Blog #ai #best #boost #developers #productivity #tools

[arammonnews]

Tabnine Brings RAG To AI Coding Assistant To Generate Contextual Code -click on the link for more details https://newszone.arammon.com/?p=27599

[maks19770926]

Tabnine - мощный помощник по кодированию искусственного интеллекта - Tabnine выделяется как мощный помощник по кодированию искусственного интеллекта, разработанный Codota. Инструмент использует алгоритмы машинного обучения для прогнозирования и предложения доработок кода, стремясь сделать кодирование более быстрым, эффективным и менее подверженным ошибкам. Одной из впечатляющих особенностей Tabnine является его совместимость с более чем 20 языками программирования. Это, наряду с возможностями интеграции с различными редакторами кода,

[thetechrobot]

This is how generative AI will free up your time at work

Can you recall a time when ChatGPT did not dominate practically every discourse concerning the future of work?

Despite its youth—OpenAI introduced the chatbot in November 2022—the generative AI tool has made a transformative impact on practically every industry, not just technology. It has a significant influence on marketing and sales, product development, and service operations.

Roughly two-thirds of workers (72%) use generative AI daily to complete tasks related to their jobs, according to a recent McKinsey study.

Around 40% of organizations employ generative AI to speed up procedures and make staff more efficient.

Potential in the Future

It’s reasonable to expect some casualties from AI’s impact—the World Economic Forum estimates that AI would result in 83 million worldwide job losses by 2027.

Accenture predicts that generative AI tools could impact 40% of working hours and automate up to 30% of employment by the mid-2030s.

While the majority of the respondents polled by McKinsey acknowledge which generative AI will cause a crucial or major impact, especially within information-based work like banking and pharmaceutical products, this impact and acceptance of new methods of working will also add 9% to global revenue.

Manufacturing-based sectors like aerospace, automotive, and advanced electronics will see less disruption.

People Also read – How to minimize data risk for generative AI and LLMs in the enterprise

Make artificial intelligence work for you

The McKinsey research also emphasizes how we’re adopting generative AI to speed up monotonous processes, allowing people to focus on more creative endeavours, which is its core benefit.

The most common use is creating initial drafts of text documents (9%), followed by personalized marketing (8%), summarizing text documents (8%), and spotting patterns in client demands (7%). ChatGPT is also used by 5% of employees to draft technical documentation and anticipate trends or anomalies, and 4% to build new product designs.

AI is transforming the IT business, particularly for software developers. Tools like CoPilot, Tabnine, and Amazon CodeWhisperer aid in the speedier and more precise creation of code. To fix bugs and prevent data breaches, CoPilot use the OpenAI Codex language model, Tabnine employs open-source code, and Amazon CodeWhisperer employs a big language model. The VentureBeat Job Board has hundreds of openings at firms that are actively hiring and deploying generative AI.

Zoom, San Jose, Machine Learning Engineer

As a Machine Learning Engineer at Zoom, you will tackle cutting-edge AI challenges and deploy models that consistently expand Zoom’s service in areas like as summarization, topic classification, language modelling, and coreference resolution. As a result, you will be required to do autonomous research with little supervision, interact with other researchers on larger-scale projects, and lead junior engineers on their research/engineering assignments.

STELLANTIS, Auburn Hills, Prompt Engineer/Generative AI Engineer

The purpose of your job as a Prompt Engineer/Generative AI Engineer is to design, create, revise, and optimize AI-generated text prompts to make sure they are correct, interesting, and relevant for a variety of applications. It contains NLP models and cues that drive language model and conversational AI system performance and effectiveness. You will use generative models and prompt engineering to develop new and creative AI products.

Apple, Cupertino, Machine Learning Engineer

Apple’s Video Computer Vision organization is developing new technologies for future Apple products, with an emphasis on ML-based solutions for real-time image and video processing. As a Machine Learning Engineer, you will help push the boundaries of 3D computer vision technologies by working with real-world data and a highly complex machine learning system to deliver computer vision neural networks and algorithms, involving training, evaluation, and failure analysis, as well as an end-to-end pipeline and metrics for fast model evaluation and repetitions.

People Also read - How to minimize data risk for generative AI and LLMs in the enterprise

#technology #generative ai #ai #customer engagement #chatgpt #virtual reality

[2anyone]

2023年最佳的30个AI工具

研究

Claude 2

ChatGPT

Perplexity

图片生成

Dall-E 3

Midjourney

Adobe Firefly

AI 写作

Jasper

CopyAI

Writesonic

AI 音频

MurfAI

Speechify

Elevenlabs

视频生成

InVideo

Synthesia

RunwayML

网站搭建

10Web

Framer

Durable

AI设计

Uizard

Clipdrop

Microsoft Designer

AI 代码助手

Tabnine

AskCodi

CodiumAI

聊天机器人

FlotAI

DanteAI

Botsonic

AI 营销

AdCopy

AdCreative

ConversionAI

转自