Interpretable Machine Learning

The emergence of machine learning as a society-changing technology in the past decade has triggered concerns about people's inability to understand the reasoning of increasingly complex models. The field of IML (interpretable machine learning) grew out of these concerns, with the goal of empowering various stakeholders to tackle use cases, such as building trust in models, performing model debugging, and generally informing real human decision-making.

Chip Measuring Contest

Alan Kay once said, "People who are really serious about software should make their own hardware." We are now seeing product companies genuinely live up to this value. It is exciting when the incumbents known as the chip vendors are being outdone, in the very technology that is their bread and butter, by their previous customers. Let's dive into some of the interesting bits of these purpose-built chips: the benefits of economics, user experience, and performance for the companies building them.

Lamboozling Attackers: A New Generation of Deception

Software engineering teams can exploit attackers' human nature by building deception environments.

I Unplugged What?

Dear KV, I'm sure by now you've read about the latest large systems failure, and I wondered if you'd share your thoughts on how such a large company can fail so miserably at infrastructure. I'm probably lobbing a softball, but how is it possible that these large and pervasive failures happen?

A Conversation with Margo Seltzer and Mike Olson

Kirk McKusick sat down with Margo Seltzer and Mike Olson to discuss the history of Berkeley DB, for which they won the ACM Software System Award in 2021. Kirk McKusick has spent his career as a BSD and FreeBSD developer. Margo Seltzer has spent her career as a professor of computer science and as an entrepreneur of database software companies. Mike Olson started his career as a software developer and later started and managed several open-source software companies. Berkeley DB is a production-quality, scalable, NoSQL, Open Source platform for embedded transactional data management.

Meaning and Context in Computer Programs

When you look at a function program's source code, how do you know what it means? Is the meaning found in the return values of the function, or is it located inside the function body? What about the function name? Answering these questions is important to understanding how to share domain knowledge among programmers using the source code as the medium. The program is the medium of communication among programmers to share their solutions.

It Takes a Community

Of the many challenges faced by open-source developers, among the most daunting are some that other programmers scarcely ever think about. Building a successful open-source community depends on many different elements, some of which are familiar to any developer. Just as important are the skills to recruit, to inspire, to mentor, to manage, and to mediate disputes. But what exactly does it take to pull all that off?

Federated Learning and Privacy

Centralized data collection can expose individuals to privacy risks and organizations to legal risks if data is not properly managed. Federated learning is a machine learning setting where multiple entities collaborate in solving a machine learning problem, under the coordination of a central server or service provider. Each client's raw data is stored locally and not exchanged or transferred; instead, focused updates intended for immediate aggregation are used to achieve the learning objective. This article provides a brief introduction to key concepts in federated learning and analytics with an emphasis on how privacy technologies may be combined in real-world systems and how their use charts a path toward societal benefit from aggregate statistics in new domains and with minimized risk to individuals and to the organizations who are custodians of the data.

Patent Absurdity

The main reason a lawyer will give for not reading a software patent is that, if you run afoul of the patent and it can be shown that you had knowledge of it, your company will incur triple the damages that they would have, had you not had knowledge of the patent. That seems like reason enough to avoid reading them, but there is an even better reason, and that is, as design or technical documents, software patents suck.

Crashproofing the Original NoSQL Key-Value Store

This episode of Drill Bits unveils a new crash-tolerance mechanism that vaults the venerable gdbm database into the league of transactional NoSQL data stores. We?ll motivate this upgrade by tracing gdbm?s history. We?ll survey the subtle science of crashproofing, navigating a minefield of traps for the unwary. We?ll arrive at a compact and rugged design that leverages modern file-system features, and we?ll tour the production-ready implementation of this design and its ergonomic interface.