cross-posted from: https://lemmy.world/post/27408560

cross-posted from: https://lemmy.world/post/27384100

The global backlash against the second Donald Trump administration keeps on growing. Canadians have boycotted US-made products, anti–Elon Musk posters have appeared across London amid widespread Tesla protests, and European officials have drastically increased military spending as US support for Ukraine falters. Dominant US tech services may be the next focus.

There are early signs that some European companies and governments are souring on their use of American cloud services provided by the three so-called hyperscalers. Between them, Google Cloud, Microsoft Azure, and Amazon Web Services (AWS) host vast swathes of the Internet and keep thousands of businesses running. However, some organizations appear to be reconsidering their use of these companies’ cloud services—including servers, storage, and databases—citing uncertainties around privacy and data access fears under the Trump administration.

“There’s a huge appetite in Europe to de-risk or decouple the over-dependence on US tech companies, because there is a concern that they could be weaponized against European interests,” says Marietje Schaake, a nonresident fellow at Stanford’s Cyber Policy Center and a former decadelong member of the European Parliament.

Russian leaders and propagandists have at once denied the existence of a Ukrainian nation and called for purging or cleansing the Ukrainian territory, in terms that often mirror rhetoric preceding past genocides. In this report, the authors seek to shed light on how Russia's extremist, hate-peddling narratives deployed in the war have spread online through social media.

Russian propaganda is making inroads into some of the major European languages—Spanish and German, as well as French and Italian.

REMVE narratives are also finding more-receptive audiences among relatively small linguistic communities in Eastern Europe. Serbian- and Bulgarian-language communities emerge as particularly vulnerable to cross-language and cross-cultural transmission of REMVE messages on both X and Telegram.

However, Russia's ability to successfully mainstream its propaganda and mobilize its audiences against Ukrainians is limited: The most virulent REMVE conversations on these two platforms remain highly Russian-language dominated, are concentrated in specific communities, and do not draw much attention from others in the networks.

Full research report: https://www.rand.org/content/dam/rand/pubs/research_reports/RRA3400/RRA3450-1/RAND_RRA3450-1.pdf

The incoming Trump administration has been supportive of this European initiative. It is consistent with the president-elect's stated desire to disengage the United States from security matters on the continent, and instead have the European Union and the United Kingdom take the lead. But a deployment of European forces to Ukraine will inevitably entangle the Americans. European militaries depend on their U.S. allies for out-of-area operations. Inevitably, a large deployment to Ukraine will once again expose this dependency when they turn to the United States for help with critical tasks such as air lift, logistics, and intelligence that they cannot conduct alone.

The Ukrainian military faces critical challenges that demand immediate, honest evaluation:

• Infantry roles becoming increasingly unsustainable

• Recruitment system disproportionately burdens vulnerable populations

• Command structures trapped in outdated bureaucratic frameworks

• Morale gradually eroding under prolonged combat stress

• No clear exit strategy for frontline soldiers

• Commanders prioritizing reporting over human lives

• Declining Western support momentum

• Deeply entrenched leadership inefficiencies

Suggested changes:

• Implement merit-based officer promotion systems
• Establish fixed, transparent service terms
• Rebuild trust between military leadership and soldiers

More in the article.

According to the article, Danieli continues to operate in Russia despite EU sanctions, collaborating with steel giants like Severstal and MMK, both linked to military production. Danieli reportedly uses its Chinese subsidiary to bypass sanctions, enabling the supply of equipment to Russia. In 2023, its Russian subsidiary’s cash flow increased 35-fold, contradicting claims that the business is unprofitable or disconnected from the military sector. The company’s justification hinges on technicalities, but the financial and strategic realities suggest complicity in sustaining critical industries that support Russia’s war economy. At what point does this move from legal maneuvering to outright enabling?

How Base 3 Computing Beats Binary

Metadata

• Author: Stephen Ornes
• Category: rss
• URL: https://www.quantamagazine.org/how-base-3-computing-beats-binary-20240809/

Highlights

Three, as Schoolhouse Rock! told children of the 1970s, is a magic number. Three little pigs; three beds, bowls and bears for Goldilocks; three Star Wars trilogies. You need at least three legs for a stool to stand on its own, and at least three points to define a triangle.

If a three-state system is so efficient, you might imagine that a four-state or five-state system would be even more so. But the more digits you require, the more space you’ll need. It turns out that ternary is the most economical of all possible integer bases for representing big numbers.

Surprisingly, if you allow a base to be any real number, and not just an integer, then the most efficient computational base is the irrational number e.

Despite its natural advantages, base 3 computing never took off, even though many mathematicians marveled at its efficiency. In 1840, an English printer, inventor, banker and self-taught mathematician named Thomas Fowler invented a ternary computing machine to calculate weighted values of taxes and interest. “After that, very little was done for years,” said Bertrand Cambou, an applied physicist at Northern Arizona University.

Why didn’t ternary computing catch on? The primary reason was convention. Even though Soviet scientists were building ternary devices, the rest of the world focused on developing hardware and software based on switching circuits — the foundation of binary computing. Binary was easier to implement.

Highlights

The first scaling crisis happened in 1996, when Linus wrote that he was "buried alive in emails". It was addressed by adopting a more modular architecture, with the introduction of loadable kernel modules, and the creation of the maintainers role, who support the contributors in ensuring that they implement the high standards of quality needed to merge their contributions.

The second scaling crisis lasted from 1998 to 2002, and was finally addressed by the adoption of BitKeeper, later replaced by Git. This distributed the job of merging contributions across the network of maintainers and contributors.

In both cases, technology was used to reduce the amount of dependencies between teams, help contributors keep a high level of autonomy, and make it easy to merge all those contributions back into the main repository, Bernhard said.

Technology can help reduce the need to communicate between teams whenever they have a dependency on another team to get their work done. Typical organizational dependencies, such as when a team relies on another team’s data, can be replaced by self-service APIs using the right technologies and architecture, Bernhard mentioned. This can be extended to more complicated dependencies, such as infrastructure provisioning, as AWS pioneered when they invented EC2, offering self-service APIs to spin up virtual servers, he added.

Another type of dependency is dealing with the challenge of merging contributions made to a similar document, whether it’s an illustration, a text, or source code, Bernhard mentioned. This has been transformed in the last 15 years by real-time collaboration software such as Google Docs and distributed versioning systems such as Git, he said.

Anyone trying to scale an agile organization should study lean thinking to benefit from decades of experience on how to lead large organizations while staying true to the spirit of the agile manifesto, he concluded.

Will be interesting to see how it works out

The Indian nonprofit People+ai wants to fix this by creating an open and interoperable marketplace of cloud providers of all sizes. The Open Cloud Compute (OCC) project plans to use open protocols and standards to allow cloud providers of all sizes to offer their services on the network. It also plans to make it easy for customers to shift between offerings depending on their needs. People+ai held a hackathon on 20 September at People’s Education Society University (PES University) in Bengaluru to test out an early prototype of the platform.

Highlights

Failure is an expected state in production systems, and no predictable failure of either software or hardware components should result in a negative experience for users. The exact failure mode may vary, but certain remediation steps must be taken after detection. A common example is when an error occurs on a server, rendering it unfit for production workloads, and requiring action to recover.

It can be tempting to rely on the expertise of world-class engineers to remediate these faults, but this would be manual, repetitive, unlikely to produce enduring value, and not scaling.

The commonality of lower-priority failures makes it obvious when the response required, as defined in runbooks, is “toilsome”. To reduce this toil, we had previously implemented a plethora of solutions to automate runbook actions such as manually-invoked shell scripts, cron jobs, and ad-hoc software services. These had grown organically over time and provided solutions on a case-by-case basis, which led to duplication of work, tight coupling, and lack of context awareness across the solutions.

A good solution would not allow only the SRE team to auto-remediate, it would empower the entire company. The key to adding self-healing capability was a generic interface for all teams to self-service and quickly remediate failures at various levels: machine, service, network, or dependencies.

Temporal is a durable execution platform which is useful to gracefully manage infrastructure failures such as network outages and transient failures in external service endpoints. This capability meant we only needed to build a way to schedule “workflow” tasks and have Temporal provide reliability guarantees.

After a workflow is validated in the staging environment, we can then do a full release to production. It seems obvious, but catching simple configuration errors before releasing has saved us many hours in development/change-related-task time.

Building a system that is maintained by several SRE teams has allowed us to iterate faster, and rapidly tackle long-standing problems. We have set ambitious goals regarding toil elimination and are on course to achieve them, which will allow us to scale faster by eliminating the human bottleneck.

Resurfaced in my feed. Obvious in retrospect.