With another new fancy AI tool, we keep getting closer to the singularity. But when it comes to programming human coders still reign supreme. Wait until machine learning solutions solve real business problems. TL;DR: , , and are leading the artificial intelligence coding segment. Alphabet's DeepMind Microsoft's Github OpenAI With different approaches, they try to solve coding challenges. They use language models to generate code. transformer-based AlphaCode an estimated rank within the top 54% of participants in programming competitions by solving new problems that require a combination of critical thinking, logic, algorithms, coding, and natural language understanding. achieved Deep Mind's product was trained and competed against humans at contests. Codeforces With overfitting claims, it outperformed several people at those contests. are available online. Results A careful look at the datasets shows basic algorithmic solutions with output code full of many human counterparts make. code smells Variables with , , , are some examples of these smells many code reviewers would not approve. bad names Lots of ifs too long methods global functions The three current solutions (AlphaCode, , ) focus on competitive programming, an area where performance is the ultimate goal and readability is not important. GitHub Copilot GPT3 The final frontier Model and business behavior instead of boring and repetitive algorithms full of code smells. domain entities Try to understand the entities and the behaviour of your simulation software. References Why GitHub Copilot is not a Threat to your Job I've Recently Learned About GPT3 - This is my Journey What should you do? Stop competing against smarter machines than you. and rich domains. Learn model You will for a few more years... keep your job

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