The Workflow Description Language (WDL) team has announced the release of WDL 1.2.0, a significant update to improve workflow descriptions' flexibility and usability in bioinformatics. This new version introduces several key features and enhancements that promise to streamline workflow management and execution, making it easier for developers and researchers to implement and manage workflows. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

In the rapidly evolving HPC landscape, the promise of quantum computing captivates researchers, industry leaders, and policymakers alike. A new paradigm is emerging as organizations seek to seamlessly blend classical and quantum computing within existing infrastructures. Quantum purchase and lease announcements from organizations such as The Cleveland Clinic, LRZ Supercomputing Center in Germany, or AIST in Japan have heightened interest in on-prem installations.

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

Richard Solomon has heard the rumblings over the years. As vice president of PCI-SIG, the organization that controls the development of the PCI-Express specification, he has listened to questions about how long it takes the group to bring the latest spec to the industry. It’s a question we raised last year, nothing the two-year cadence CPU and GPU makers have for releasing the latest and greatest silicon, not to mention the chip makers for network switching and interface cards for Ethernet and InfiniBand.

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

Meta created an internal toolkit to help improve the accuracy of AI predictions. Its engineers say it has a hefty set of features that makes a big difference. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

Midjourney model personalization is now live, offering you a more tailored image generation experience by teaching the AI your preferences. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

We asked a prominent data scientist to put together a concrete example of fine-tuning an LLM, aimed at people who are not computer programmers, with an emphasis on the implications for a business that wants to fine-tune a model. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

Remote.It's new Scripting API solution leverages GraphQL to empower the overseeing and enhancing an extensive range of devices, including IoT devices deployed in incredibly diverse environments. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

Demystify the world of data quality management and the role of data testing, monitoring, and observability in ensuring accurate data. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

Mistral AI, one of Europe’s premier artificial intelligence startups, has marked its entry into the programming and development space with the launch of Codestral, an open-weight generative AI model explicitly designed for code generation tasks. 

Trained on a dataset of 80 programming languages, Codestral is designed for various coding functions and can complete any partial code using a fill-in-the-middle mechanism, according to a blog post released by Mistral. Developers can also use the model as a learning tool to improve their coding skills and minimize errors.

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

Large Language Models (LLMs) can do astonishing things, like summarize complex data or generate creative content in seconds. Unfortunately, they also make things up— euphemistically referred to as hallucinating. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

The idea of solving the biggest robotics challenges by training large models is sparking debate 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

The proliferation of AI means we need a new word. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

LibreChat levels the field for generative AI, allowing users to pick their favorite AI providers, services, and integrations. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

There are really two stories packaged in the most recent MLPerf Training 4.0 results, released today. The first, of course, is the results. Nvidia (currently king of accelerated computing) wins again, sweeping all nine “events” (workflows) as it were. Its lead remains formidable. Story number two, perhaps more important, is MLPerf itself. It has matured through the years to become a far more useful broad tool to evaluate competing ML-centric systems and operating environments.

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

El Reg queries author Matei Zaharia on a decade of the project

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

A newly-published survey of app developers suggests that the lines between architectures relied on to build applications continue to blur. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

Transform Intelligent Transportation Systems with blockchain solutions. Improve security, transparency, and efficiency in traffic management. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

Consider the GPU. An island of SIMD greatness that makes light work of matrix math. Originally designed to rapidly paint dots on a computer monitor, it was then found to be quite useful in large numbers by HPC practitioners. Enter GenAI, and now these little matrix mavens are in huge demand, so much so that we call it the GPU Squeeze.

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

Today, the use of AI for image classification tasks has become ubiquitous. Millions of images are processed daily with increasing quality standards. However, beyond the quality of classification, optimizing other aspects such as model speed is crucial. Here, we delve into the proper optimization techniques for high-performance ML image preprocessing, focusing on 5 key methods.

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

There is much ado these days regarding the language facility popular AI tools such as ChatGPT, Midjourney, Microsoft Copilot, and Gemini Connected appear to display. What do these systems comprehend? Do they understand? Are the underlying architectures a big leap toward artificial general intelligence (AGI) or an entertaining dead end? This article is not about that. This is a loosely related thread on how the language we use to describe AI systems affects our ability to govern them effectively. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

A new survey of C-suite executives and AI leaders shows while enterprise decision-makers trust the potential of AI, many lack confidence in their company’s strategy to execute as well as the data readiness to ensure reliability of AI outputs. Moreover, 7 in 10 executives say their AI strategy is not fully aligned to their business strategy today. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

According to the World Health Organization, 280 million people suffer from depression worldwide. More than half of those people aren’t diagnosed or treated because of the cost of care and effort involved in pursuing treatment. Fitness trackers can play a role in screening for depression and anxiety. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

Increasingly stringent privacy regulations—for example, GDPR (General Data Protection Regulation) in the European Union; and CCPA (California Consumer Privacy Act)—and sophisticated attacks leading to massive breaches have increased the demand for protecting data in use, or encryption in use. The encryption-in-use paradigm is important for security because encryption at rest protects that data only when it is in storage and encryption in transit protects the data only when it is being communicated over the network. In both cases, however, the data is exposed during computation—namely, while it is being used/processed at the servers. That processing window is the time when many data breaches happen, either at the hands of hackers or insider attackers.

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

With organizations of all sorts facing increased urgency and unpredictability, being able to ask smart questions has become key. But unlike lawyers, doctors, and psychologists, business professionals are not formally trained on what kinds of questions to ask when approaching a problem. They must learn as they go. In their research and consulting, the authors have seen that certain kinds of questions have gained resonance across the business world. In a three-year project they asked executives to brainstorm about the decisions they’ve faced and the kinds of inquiry they’ve pursued. In this article they share what they’ve learned and offer a practical framework for the five types of questions to ask during strategic decision-making: investigative, speculative, productive, interpretive, and subjective. By attending to each, leaders and teams can become more likely to cover all the areas that need to be explored, and they’ll surface information and options they might otherwise have missed. 

@tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X