Author: Admin

(As part of this series, join MIT Technology Review’s editor in chief, Mat Honan, and editor at large, David Rotman, for an exclusive conversation with Financial Times columnist Richard Waters on how AI is reshaping the global economy. Live on Tuesday, December 9 at 1:00 p.m. ET. This is a subscriber-only event and you can sign up here.) Will Douglas Heaven writes:  Every time I’m asked what’s coming next, I get a Luke Haines song stuck in my head: “Please don’t ask me about the future / I am not a fortune teller.” But here goes. What will things be…

Global talent models are being tested by a complex web of policy shifts and geopolitical volatility. Visa reforms, contractor reclassification, tariff disputes, and regional conflicts are redefining how and where organizations access talent. From tightening H-1B scrutiny in the United States to Brazil’s evolving labor rules and renewed trade tensions across major economies, disruption has become the backdrop of global workforce planning. The question for organizations is no longer whether uncertainty will persist but how prepared their talent management models are to absorb it. The new reality: Policy and geopolitical uncertainty Across geographies, governments are reshaping labor and trade frameworks…

In this article, you will learn practical prompt-engineering patterns that make large language models useful and reliable for time series analysis and forecasting. Topics we will cover include: How to frame temporal context and extract useful signals How to combine LLM reasoning with classical statistical models How to structure data and prompts for forecasting, anomalies, and domain constraints Without further delay, let’s begin. Prompt Engineering for Time Series AnalysisImage by Editor Introduction Strange as it may sound, large language models (LLMs) can be leveraged for data analysis tasks, including specific scenarios such as time series analysis. The key is to…

We are extending Azure public regions with options that adapt to our customers’ evolving business requirements without forcing trade-offs. Organizations running mission‑critical workloads operate under stricter standards because system failures can often affect people and business operations at scale. They must ensure control, resilience, and operational autonomy such that innovation does not compromise governance. They need agility that also maintains continuity and preserves standards compliance, so they can get the most out of AI, scalable compute, and advanced analytics on their terms. For example, manufacturing plants need assembly lines to continue to operate during network outages, and healthcare providers need…

The Amazon EMR runtime for Apache Spark is a performance-optimized runtime for Apache Spark that is 100% API compatible with open source Apache Spark. With Amazon EMR release 7.9.0, the EMR runtime for Apache Spark introduces significant performance improvements for encrypted workloads, supporting Spark version 3.5.5. For compliance and security requirements, many customers need to enable Apache Spark’s local storage encryption (spark.io.encryption.enabled = true) in addition to Amazon Simple Storage Service (Amazon S3) encryption (such as server-side encryption (SSE) or AWS Key Management Service (AWS KMS)). This feature encrypts shuffle files, cached data, and other intermediate data written to local…

We have covered packer-as-a-service offerings from the computer underworld in the past, previously dissecting impersonation campaigns and the rise of HeartCrypt, both popular among ransomware groups. However, it is a fast-changing landscape, and now we are watching a new incarnation of the same type of service: the Shanya crypter — already favored by ransomware groups and taking over (to some degree) the role that HeartCrypt has played in the ransomware toolkit. We’ll look at its apparent origins, unpack the code, and examine a targeted infection leveraging this tool. Sophos protections against this specific packer are covered at the end of…

Seven Regional Clean Energy Companies Graduate from Cleantech San Diego Startup Accelerator Shannon Bresnahan   |   Press Releases SAN DIEGO, CA, March 11, 2025 – Cleantech San Diego today announced the graduation of seven local clean energy companies – ChargeNet Stations, Helicoid, Paired Power, Redoxblox, Sonocharge, Uprise Energy, and Xtelligent – from its Southern California Energy Innovation Network (SCEIN).   SCEIN is an accelerator program for clean energy startups based in San Diego, Riverside, San Bernardino, and Imperial counties that are developing technologies to help California meet its clean energy goals. The program offers free business services through a consortium of regional…

The ternary operator is one of those things that will exist in virtually any modern programming language. When writing code, a common goal is to make sure that your code is succinct and no more verbose than it needs to be. A ternary expression is a useful tool to achieve this.What is a ternary?Ternaries are essentially a quick way to write an if statement on a single line. For example, if you want to tint a SwiftUI button based on a specific condition, your code might look a bit as follows:struct SampleView: View { @State var username = “” var…

Artificial Intelligence (AI) at the edge is popular among smart video devices. For example, Smart Home cameras and video doorbells revolutionized home monitoring. What began as simple recording and remote viewing tools has evolved into intelligent observers. With AI infusion, today’s cameras can actively analyze scenes, alert users to motion events, recognize familiar faces, spot package deliveries, and dynamically adjust their recording behavior. Enterprise surveillance cameras are another example. These cameras have superior resolution, enhanced computing power, and can drive more sophisticated AI models. These enhanced capabilities result in sharper detection at greater distances. As illustrated, customers demand intelligent monitoring…

While the training of large language models provides deep knowledge that is excellent for common tasks—like creating Compose UIs—training concludes on a fixed date, resulting in gaps for new libraries and updated best practices. They are also less effective with niche APIs because the necessary training data is scarce. To fix this, Android Studio’s Agent Mode is now equipped with the Android Knowledge Base, a new feature designed to significantly improve accuracy and reduce hallucinations by grounding responses with authoritative documentation. This means that instead of just relying on its training data, the agent can actively consult fresh documentation from…