[Dev Catch Up #29] - Fine-tuning in GPT-4o, GitHub Copilot Autofix, Unveiling Grok-2, and much more.
Bringing devs up to speed on the latest dev news from the trends including, a bunch of exciting developments and articles.
Welcome to the 29th edition of DevShorts, Dev Catch Up!
I write about developer stories and open source, partly from my work and experience interacting with people all over the globe.
Some recent issues from Dev Catch up:
LLM training at Meta, iOS 18 beta release, AI security with PCC
Federated Language Models, Speculative Decoding API, AI in Figma
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Must Read
Recently, OpenAI brought a huge update to their most powerful model that will benefit the developers using the model in their applications immensely. Fine-tuning is now available for GPT-4o and you will be able to fine-tune custom versions of GPT-4o. To those unfamiliar, fine-tuning in machine learning refers to a process in which you take a pre-trained model and make adjustments in that model to perform specific tasks or improve its performance on a given dataset. With fine-tuning available in GPT-4o, developers will be able to fine-tune the model with custom datasets and get a higher performance with lower costs for specific use cases. It also enables the model to customize structure and tone of responses and help developers generate strong results with very few examples in their training sets. Learn more about fine-tuning in GPT-4o from this detailed article from the OpenAI team, where they explained in detail about the feature along with its advantages.
AI-powered coding assistants are powering developers to be more productive than usual and in this race, GitHub Copilot holds quite a big share. In a recent move, they announced the general availability of their AI-powered remediation with Copilot Autofix. Previously, there were code scanning tools that detected the vulnerabilities but the problem was their inability to offer a solution to fix them. Copilot Autofix detects vulnerabilities in a codebase and offers a detailed explanation along with code suggestions that help developers fix those vulnerabilities as soon as they are found. With this feature, fixing vulnerabilities is expected to become 3x faster among developers. Learn more about Autofix from this well-explained article published by GitHub detailing the usage and advantages of the feature along with a demo video.
As the race towards the generation of the most powerful and capable Large Language Model continues, big organizations are pouring billions to get the best one out. In this race, although entered slowly, Elon Musk owned micro-blogging platform X is steadily gaining its ground with the introduction of their most powerful and advanced model yet, Grok-2. The new version of Grok also comes with a mini version of the same model with the name of Grok-2 mini. X claimed that Grok 2 is a significant advancement from their previous model Grok-1.5 with frontier capabilities in coding, chatting, and reasoning. It also claimed that the model has outperformed Claude 3.5 Sonnet and GPT-4-Turbo in the leaderboard and will be available to developers through X’s enterprise API later. Learn more about the capabilities of Grok-2 from this explanatory article published by Team X, where more details on the model and its performance has been given.
Now, we will head over to some of the news and articles that will be at a place of interest for developers and the tech community out there.
Good to know
Since AI and ML have been such an important part in our everyday life, it is important to learn the different concepts of the technology. Quantization is one such concept which is defined as a process in machine learning that reduces the precision of the numbers used to represent the model’s parameters and the computations performed within the model. The main goal is to increase the efficiency of the model and reduce the computational and memory demands for running a model. Since, there are no one-size-fits-all solutions to quantization, it is often tailor made based on certain use-cases for the model. Hence, there are a variety of quantization techniques and potential parts of a model to quantize. Fireworks.AI have published a wonderful article detailing the different quantization techniques and how it works with different individual customers to evaluate quantization precisely and interpretably.
Monitoring is one of the most important aspects when it comes to assessing the health and proper functioning of an application. In a Kubernetes environment, data like metrics and logs help monitor an application. But there are also Kubernetes events, with the help of which information can be obtained about the operation of components. Events store information about Pods, Worker Nodes, and Kubernetes Schedulers. You can monitor with the help of logs and metrics using popular monitoring and observability tools like Grafana. The same can be used to monitor events alongside kubectl, the Kubernetes command-line interface. Learn more about how you can monitor events with the help of kubectl and Grafana Loki from this detailed article published by Arseny Zinchenko, where he has presented a step-by-step guide on the matter.
Open-Source projects are one of the lifelines for modern software development. It is our duty to bring them to the limelight and celebrate their development as milestones. With that in mind, this week, we are looking into this open-source project that makes it easy for developers to handle remote machines and SSH keys. The tool named Viking makes things simple for developers to work with bare-metal servers. It allows full control for the developers to make most of the server’s resources. Checkout the project from its GitHub link here and leave a star to support it.
Lastly, we will take a look at some of the trending scoops that hold a special mention for the community.
Notable FYIs
AI has shaped today’s world with the introduction of LLMs and there has been a significant upgrade in the world of image and video segmentation with the introduction of the second version of the Segment Anything Model. This model is open-source and learn more about this model and its implementation from this podcast episode published by Latent Space.
Changelogs are effective for documenting the updates of different releases for a particular software and hence maintaining one requires a lot of effort. This detailed article from Xavd shows a complete view on how changelogs should be written along with the do’s and don'ts that needs to be followed while writing one.
A reliable software design is highly essential for creating a fully functional application that enriches user experience and productivity. Hence, some best practices must be followed while designing an application and this article from Two Wrongs lists some of the effective best practices that you need to follow while designing your application.
Kubernetes is the de facto orchestration platform and its usage comes with challenges. To combat these challenges, there are design patterns that are reusable solutions to common problems that occur while managing an application in a Kubernetes environment. Here is a short article from ByteByteGo that discusses the different design patterns that are available for usage.
Cloud native engineering is an exciting field and attending a conference topped with sessions on of the technologies is a treat for developers and devops people. GitOps is a technology that has helped development by folds and tools like ArgoCD and others are the flag bearer. Tune into an insight packed session with the developers of Argo in ArgoCon, which is happening on the sidelines of KubeCon NA. Grab your tickets from the official CNCF site.
That’s it from us with this edition. We hope you are going away with a ton of new information. Lastly, share this newsletter with your colleagues and pals if you find it valuable and a subscription to the newsletter will be awesome if you are reading for the first time.