At its ongoing re:Invent 2023 conference, AWS unveiled several updates to its SageMaker, Bedrock and database services in order to boost its generative AI offerings.

Taking to the stage on Wednesday, AWS vice president of data and AI, Swami Sivasubramanian, unveiled updates to existing foundation models inside its generative AI application-building service, Amazon Bedrock.

The updated models added to Bedrock include Anthropic’s Claude 2.1 and Meta Llama 2 70B, both of which have been made generally available. Amazon also has added its proprietary Titan Text Lite and Titan Text Express foundation models to Bedrock.

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Keras 3.0, a “full rewrite” of the Keras deep learning API, has arrived, providing a new multi back-end implementation of the API.

Unveiled November 27, and accessible from GitHub, Keras 3.0 enables developers to run Keras workflows on top of the Jax, TensorFlow, or PyTorch machine learning frameworks, featuring large-scale model training and deployment capabilities. Keras is deployed as a low-level cross-framework language to develop custom components such as layers, models, or metrics that can be used in native workflows in all three frameworks, with one codebase.

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Microsoft has released ML.NET 3.0, the latest version of the company’s open-source, cross-platform machine learning framework, which enables the integration of machine learning models into .NET applications.

Announced November 27, ML.NET 3.0 can be accessed from dotnet.microsoft.com.

ML.NET 3.0 includes new deep learning capabilities in object detection, named entity recognition, and question answering. Support for these deep learning scenarios was enabled via integrations and interoperability with TorchSharp and ONNX models. The 3.0 release also updates integration with the LightGBM gradient boosting framework.

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Structured concurrency is a new way to use multithreading in Java. It allows developers to think about work in logical groups while taking advantage of both traditional and virtual threads. Available in preview in Java 21, structured concurrency is a key aspect of Java’s future, so now is a good time to start working with it.

Why we need structured concurrency

Writing concurrent software is one of the greatest challenges for software developers. Java’s thread model makes it a strong contender among concurrent languages, but multithreading has always been inherently tricky. Structured concurrency allows you to use multiple threads with structured programming syntax. In essence, it provides a way to write concurrent software using familiar program flows and constructs. This lets developers focus on the business at hand, instead of the orchestration of threading. As the JEP for structured concurrency says, "If a task splits into concurrent subtasks then they all return to the same place, namely the task's code block."

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When it comes to working with data in a tabular form, most people reach for a spreadsheet. That's not a bad choice: Microsoft Excel and similar programs are familiar and loaded with functionality for massaging tables of data. But what if you want more control, precision, and power than Excel alone delivers?

In that case, the open source Pandas library for Python might be what you are looking for. It outfits Python with new data types for loading data fast from tabular sources, and for manipulating, aligning, merging, and doing other processing at scale.

Your first Pandas data set

Pandas is not part of the Python standard library. It's a third-party project, so you'll need to install it in your Python runtime with pip install pandas. Once installed, you can import it into Python with import pandas. 

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During its dozen-plus years in the wild, Google’s Go programming language has evolved from being a curiosity for alpha geeks to being the battle-tested programming language behind some of the world’s most important cloud-native software projects. 

Why was Go chosen by the developers of such projects as Docker and Kubernetes? What are Go’s defining characteristics, and how does it differ from other programming languages? What kinds of projects is Go most suitable for? In this article, we’ll explore Go’s feature set, the optimal use cases, the language’s omissions and limitations, and where Go may be going from here.

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Continuing to build on its efforts toward zero-ETL for data warehousing services, AWS at its ongoing re:Invent 2023 conference, announced new Amazon RedShift integrations with Amazon Aurora PostgreSQL, Amazon DynamoDB, and Amazon RDS for MySQL.

Enterprises, typically, use extract, transform, load (ETL) to integrate data from multiple sources into a single consistent data store to be loaded into a data warehouse for analysis.

However, most data engineers claim that transforming data from disparate sources could be a difficult and time-consuming task as the process involves steps such as cleaning, filtering, reshaping, and summarizing the raw data.

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Java Development Kit 22, set to arrive in March 2024 as the next version of Java Standard Edition, has grown to include 10 features so far, with a second preview of structured concurrency and an enhancement to the Java application launcher proposed in the past few days.

A possible 11th feature, stream gatherers, has been tentatively designated for JDK 22 but was not listed yet on the official JDK 22 OpenJDK web page as of November 27.

These latest features join a preview of statements before super(…), a preview of a class-file API, region pinning for the G1 garbage collector, a second preview of string templates, unnamed variables and patterns, a foreign function and memory API, and a seventh incubator of a vector API. A second preview of implicitly declared classes and instance main methods also has been proposed.

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At its ongoing re:Invent 2023 conference, AWS on Monday added a new enterprise pricing tier to its cloud-based development tool, dubbed Amazon CodeCatalyst.

The enterprise tier is $20 per user per month, and each enterprise tier space gets 1,500 compute minutes, 160 development environment hours, and 64GB of development environment storage per paying user, the cloud services provider said.

The other tiers available include the free tier and the standard tier. While the free tier allows usage of up to 2,000 compute minutes, 60 development environment hours, and a maximum aggregate limit of 64 GB of development environment storage, the standard tier, which costs $4/user per month, allows usage of up to 3,000 compute minutes, 200 development environment hours, and a maximum aggregate limit of 128GB of development environment storage.  

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At its ongoing re:Invent 2023 conference, AWS on Monday announced a new program, dubbed Amazon Braket Direct to offer researchers direct, private access to quantum computers.

The program is part of AWS’ managed quantum computing service, named Amazon Braket, which was introduced in 2020. 

Amazon Bracket Direct allows researchers across enterprises to get private access to the full capacity of various quantum processing units (QPUs) without any wait time and also provides the option to receive expert guidance for their workloads from AWS’ team of quantum computing specialists, AWS said.

Currently, the Direct program supports the reservation of IonQ Aria, QuEra Aquila, and Rigetti Aspen-M-3 quantum computers.

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This week is AWS re: Invent in Las Vegas (better called “cloud computing Woodstock”). The crowd grows yearly, and it’s a “must-attend” event for the cloud computing crowd.

I typically avoid these. You can get the same information remotely these days, and you can see all of the event online; it’s a better approach if you’re trying to get the complete picture. However, attending in person does let you feel the excitement, which is why these events exist, which are mostly loss leaders for the cloud and technology providers.

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In our post-pandemic, digital world, small and medium-sized businesses (SMBs) have migrated to the cloud in droves to take advantage of the same tools and efficiencies as large-scale enterprises. Still, according to Accenture, basic cloud adoption across all businesses is at 44% globally, indicating there’s still an enormous opportunity for digital transformation in the cloud. So, what’s the hitch?

Often, SMBs are concerned with paying for more services than they need, securing and retaining the right talent, or the security of their data in the cloud. These are exactly the kinds of considerations that should be top of mind for SMB leaders.

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ASP.NET Core offers a simplified hosting model, called minimal APIs, that allows us to build lightweight APIs with minimal dependencies. Minimal APIs are ideal for building microservices and fast HTTP APIs. Naturally, you will often need to secure the endpoints of such APIs in your applications. The goal of this post is to give you a head start on doing so.

We have discussed how to get started with minimal APIs, how to use logging and dependency injection in minimal APIs, and how to test minimal APIs in earlier articles. This article discusses how we can secure our minimal API endpoints using JWT authentication—i.e., authentication based on JSON Web Tokens.

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Developers can now use simple natural language to build or enhance chatbots with Amazon Lex, a tool for crafting conversational interfaces. Using new generative AI features, programmers can describe tasks they want the service to perform, like "organize a hotel booking including guest details and payment method," as highlighted in a recent blog post by the company.

“Without generative AI, the bot developer would have to manually design each element of the bot — intents or possible paths, utterances that would trigger a path, slots for information to capture, and prompts or bot response, among other elements,” Sandeep Srinivasan, a senior product manager of Amazon Lex at AWS, said in an interview. “With this approach, you get started easily.”

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PHP 8.3, a major update to the popular server-side web scripting language, offers features such as explicit typing of class constants, deep cloning of readonly properties, and additions to randomness functionality.

Released November 23, PHP 8.3 can be accessed from php.net.

With typed class constants, PHP 8.3 gains support for declaring class, interface, trait, and enum constant types. Class constant type declarations support all type declarations supported by PHP, with the exception of void, callable, and never.  The void and callable types are not supported due to issues discussed in the typed properties v2 RFC. Similarly, never is not applicable in the context of constants.

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For decades, when I got to work in the morning, I would start Microsoft Visual Studio (or one of its predecessors, such as Visual C++ or Visual InterDev), then brew tea and possibly attend a morning meeting while it went through its laborious startup. I would keep the IDE open all day as I went through develop/test/debug cycles to avoid another startup delay. When I worked on a C++ project with ~2 million lines of code, I also jump-started each day’s work by automatically running a batch script that did a code checkout and full rebuild of the product in the wee hours.

The startup overhead of Visual Studio has decreased significantly over the years, by the way. It’s now a non-issue even in huge Visual Studio 2022 projects.

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Sometimes AI hype can be so silly that it distracts us from the important work of making it functional. For example, you can read Bill Gates’ paean to AI and believe that within the next five years, “You’ll simply tell your device, in everyday language, what you want to do.” Of course! And maybe you’ll issue those commands while sitting in one of Elon Musk’s fully autonomous self-driving cars that he’s been promising forever (well, for 10 years, to be fair).

In our rush to hype the AI future, we risk setting unrealistic expectations that can have a dampening impact on investment, particularly in areas of security. Even if we reach Bill Gates’ utopia, it will feel more like a dystopia if we can’t fix things like prompt injection for large language models (LLMs).

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Large language models (LLMs) can understand and generate human language. These generative AI tools are powerful and popular, with over 90% of retail and ecommerce leaders reporting using them to assist with work tasks, according to a recent Future Commerce report.

For example, LLMs can generate different versions of a product description for different types of customers—such as those interested in sustainability, price or style—helping ecommerce businesses personalize their engagement and therefore drive more revenue. LLMs received a $10.5 billion valuation in 2022, and experts predict their valuation will reach $40.8 billion by 2029.

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If there is anything that keeps cloud development leaders up at night, it’s the fact that the risk of an impending security breach is scarily high. If I go around the room at any enterprise development meeting, devops engineers, cloud developers, and cloud architects all see a company-debilitating breach as inevitable.

Enterprise Strategy Group recently completed a cloud threat detection and response research project with interesting results. First, what we already understand: 80% of organizations have adopted a devops model, and 75% push new software builds to production at least once a week. The top challenges include not having enough visibility and control within the development process, software released without security checks, and inconsistent security processes across development teams. I would add supply chain concerns as well.

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Microsoft Azure has been at the heart of Microsoft’s AI ambitions for many years now. It began with making the deep learning products of Microsoft Research available as Azure Cognitive Services. Then Microsoft added tools to roll your own cloud-hosted machine learning, using Azure to train models and host the resulting services. Now Azure is the home for Microsoft’s growing family of Copilots, which both build on Azure OpenAI’s generative AI models and give customers access to those same models.

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Writing reusable code is a vital skill for every software developer, and every engineer must know how to maximize code reuse. Nowadays, developers often use the excuse that there is no need to bother with writing high-quality code because microservices are inherently small and efficient. However, even microservices can grow quite large, and the time required to read and understand the code will soon be 10 times more than when it was first written.

Solving bugs or adding new features takes considerably more work when your code is not well-written from the start. In extreme cases, I've seen teams throw away the whole application and start fresh with new code. Not only is time wasted when this happens, but developers are blamed and may lose their jobs.

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Generative AI, the wave of artificial intelligence led by OpenAI’s GPT large language models and ChatGPT, is experiencing rapid, never-before-seen levels of adoption, according to a report from technology publisher and training provider O’Reilly. But issues remain with adoption, including lack of perceived business cases and worrisome legal questions.

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The Happy Hacking Keyboard line from PFU America is aimed at users who want a compact, but powerful and customizable keyboard with a great typing feel. The latest version of the HHKB (as it's abbreviated) is the HHKB Studio, designed to compress both keyboard and mouse functionality into the most compact footprint possible. Like its predecessors, this keyboard isn't cheap—its list price is $385—but it offers a mix of features you won't find in other keyboards.

Let's take a look.

HHKB Studio test drive

The HHKB Studio uses USB-C or Bluetooth and battery-powered connections, with both cabling and batteries included. Bluetooth pairing works with up to four distinct devices, and it can be used to command both Mac and Windows systems interchangeably.

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Everything in Java is an object, except primitives like int. Turns out that small caveat has big implications for the language, which have compounded over the years. This seemingly minor design decision causes problems in key areas like collections and generics. It also limits certain performance optimizations. Project Valhalla, the Java language refactor, aims to correct these issues. Valhalla project lead Brian Goetz has said that Valhalla will “heal the rift between primitives and objects."

It’s fair to say Project Valhalla is an epic refactor, seeking to address technical debt buried deep in the platform since Java’s inception. This thoroughgoing evolution proves that Java is not only a classic but remains at the forefront of programming language design. Let's take a look at the key technical components of Project Valhalla and why they are so critical to the future of Java.

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TypeScript 5.3, an upgrade to Microsoft’s strongly typed JavaScript variant that adds support for import attributes for ECMAScript modules, is now available as a production release.

TypeScript 5.3 also offers features ranging from stable support for resolution mode in import types to interactive inlay hints for types. Announced November 20, the production release can be accessed through NuGet or NPM. The NPM command:

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My colleague Paul Krill does a great job rounding up the highest-paid cloud computing certifications you can obtain these days. In other words, by passing these courses, you’ll likely have no problem finding a well-paying job.

While there are a few non-brand-related certifications on his list, most are specific to a cloud provider, focusing on particular security services, database services, devops services, etc. I get why this is a thing. Those seeking cloud talent are given marching orders from IT leaders with very narrow requirements, usually certain cloud computing capabilities, so those are the certifications they seek.

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Historically, working with big data has been quite a challenge. Companies that wanted to tap big data sets faced significant performance overhead relating to data processing. Specifically, moving data between different tools and systems required leveraging different programming languages, network protocols, and file formats. Converting this data at each step in the data pipeline was costly and inefficient.

Enter Apache Arrow, an open-source framework that defines an in-memory columnar data format that every analytical processing engine can use.

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The unique approach of the Rust programming language results in better code with fewer compromises than C, C++, Go, and the other languages you probably use. It also gets updated regularly, often every month.

Where to download the latest Rust version

If you already have a previous version of Rust installed via rustup, you can access the latest version via the following command:

$ rustup update stable

The new features in Rust 1.74.0

Unveiled November 16, Rust 1.74.0 homes in on the Cargo package manager with several features. Rust 1.74.0 offers lint configuration through Cargo. The Cargo.toml manifest now supports a [lints] table to configure the reporting level (forbid, deny, warn, allow) for lints from the compiler and other tools. With this capability, there is no need to set RUSTFLAGS (-F, -D, -W, -A), which would affect an entire build, or use create-level attributes such as:

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