Daily Tech Digest - February 13, 2023

Mergers and Acquisitions in Healthcare: The Security Risks

Incidents such as the CommonSpirit ransomware attack highlight the critical importance for entities to carefully assess and address potential IT security risks involving a potential merger or acquisition, experts say. "We are seeing that well-established health systems or entities that have very mature cybersecurity programs take on an entity which is less secure," says John Riggi, national adviser for cybersecurity and risk at the American Hospital Association. The association advises hospital mergers to treat cyber risk with the same priority as financial analysis in a merger. But determining and identifying the array of systems and myriad of devices used by another healthcare entity that's being acquired is not easy. "When you buy an organization, you typically don't know everything you're buying," says Kathy Hughes, CISO of New York-based Northwell Health, which has 21 hospitals and over 550 outpatient facilities, many of which were acquired by the organization, which is the result of a 1997 merger between North Shore Health System and Long Island Jewish Medical Center.

Forget ChatGPT vs Bard, The Real Battle is GPUs vs TPUs

Solving for efficient matrix multiplication can cut down on the amount of compute resources required for training and inferencing tasks. While other methods like quantisation and model shrinking have also proven to cut down on compute, they sacrifice on accuracy. For a tech giant creating a state-of-the-art model, they’d rather spend the $5 million, if there’s no way to cut costs.  ... NVIDIA’s GPUs were well-suited to matrix multiplication tasks due to their hardware architecture, as they were able to effectively parallelise across multiple CUDA cores. Training models on GPUs became the status quo for deep learning in 2012, and the industry has never looked back. Building on this, Google also launched the first version of the tensor processing unit (TPU) in 2016, which contains custom ASICs (application-specific integrated circuits) optimised for tensor calculations. In addition to this optimisation, TPUs also work extremely well with Google’s TensorFlow framework; the tool of choice for machine learning engineers at the company.

As Digital Trade Expands, Data Governance Fragments

The upshot is that we are still far from any more global efforts. Even preliminary convergence on national laws about data protection and privacy between the United States and the European Union is difficult to achieve. Instead, Aaronson advocated for the establishment of a new international organization that could provide proper incentives to, and pay, global firms to share data. Overall, the panellists urged that technical discussions of data flows, data governance and rules for digital trade be contextualized within fundamental concerns about the nature of data and the role of human rights. These concerns equally require attention and governance. The discussion on effective digital governance requires a fundamental rethink of the nature of data. As emphasized by panellist Kyung Sin Park, data embeds fundamental human freedoms and human information. It is closely linked to human rights. Data is much more than an economic asset used in training artificial intelligence (AI) algorithms.

Fall in Love with the Problem, Not the Solution: A Handbook for Entrepreneurs

Think of a problem—a big problem, something worth solving, something that would make the world a better place. Ask yourself, who has this problem? If you happen to be the only person on the planet with this problem, then go to a shrink. It’s much cheaper and easier than building a startup. But if a lot of people have this problem, go and speak with those people to understand their perception of the problem. Know the reality, and only then start building the solution. If you follow this path and your solution works, it’s guaranteed to create value. But there is a more important part to this. Imagine speaking with people and their feedback is, yeah, go ahead and solve that for me—this is a big problem. All of a sudden you feel committed to this journey. You essentially fall in love with the problem. Falling in love with the problem dramatically increases your likelihood of being successful because the problem becomes the north star of your journey, keeping you focused.

Data Mobility Framework: Expert Offers Four Keys to Know

It’s common for hybrid work teams to schedule when employees will be in the office and when they’ll work remotely. But while remote workers don’t always work from the same home office, they do expect similar access to business data and applications regardless of the network or device they’re using—and all of this remote connectivity has a material impact on data storage demands. Organizations try to balance data storage initiatives to address this without causing downtime to mission-critical applications and data. The faster organizations can add new storage or move data non-disruptively to another location, the better services they can deliver to end-users. Thankfully, the right data migration partner can perform these critical services non-disruptively in a matter of hours. This enables the organization and its partners to access a range of capabilities to minimize data migration efforts, including being able to migrate “hot data” to a new, more powerful array without downtime. Hot data is any data that is in constant demand, such as a database or application that’s essential for your business to operate.

Stop Suffocating Success! 7 Ways Established Businesses Can Start Thinking Like a Startup.

Startups aren't trapped by old rules—they're in the process of inventing themselves. Obviously, established companies can't just completely throw out the rulebook. But remember rules should exist to help, not just because they've always been there. Otherwise, people wind up blindly following often annoying processes without thinking about the end goal. For example, if multiple clients ask for a product feature that hasn't been included, but there isn't a feature review meeting until the next quarter, does it make sense to follow the rules and wait? Or should staff be empowered to add the feature (or, at least, fast-track a product review)? Beware of any policy that exists because "We've-always-done-things-this-way." ... Incompetent workers can take a terrible toll. To start, everything's harder when the people around you don't carry their weight. It's also demoralizing—you're working so hard and hitting all your goals, while the person next to you fails spectacularly and apparently isn't penalized for it. Over time, you're likely to grow bitter or just stop trying so hard since results clearly don't matter.

The Stubborn Immaturity of Edge Computing

Of course, they don’t even think of it as “the edge”. To them, it’s where real work takes place. So when IT vendors and cloud providers and carriers talk about the “far edge” (where real customers and real factories and real work takes place), that makes no sense to people outside of IT vendors’ data-center-centric bubble. The real world doesn’t revolve around the data center, or the cloud. What’s really far in the real world? The cloud. The data center. Edge computing is a technology style that’s part of a digital transformation trend. Digital transformation has been on a march for decades, well before we called it that. It’s accelerated because of cloud computing, and global connectivity. A lot of the technology transformation has been taking place at the back-end. In data centers, in business models. And there’s a lot left to be done. But the true green field in digital transformation is where people and things and factories actually exist. (OK, we’ll call that the “edge”, but that’s such an old IT-centric way of talking!)

How the Future of Work Will Be Shaped by No Code AI

No-code, like other breakthroughs, is a thrilling disruption and improvement in the software development process, particularly for small firms. Among its various applications, no-code has enabled users with little technical experience to create applications using pre-built frameworks and templates, which will undoubtedly lead to further inventions and design and development in the digital town square. It also cuts down on software development time, allowing for faster implementation of business solutions. Aside from the time saved, no-code can enhance computer and human resources by transferring these duties to software suppliers. ... No-code is also a game changer for many AI technology developers and non-technical people since it focuses on something we never imagined possible in the difficult field of artificial intelligence: simplicity. Anyone will be able to swiftly build AI apps using no-code development platforms, which provide a visual, code-free, and easy-to-use interface for deploying AI and machine learning models.

Code Readability vs Performance: Here is The Verdict

Code performance is critical, especially when working on projects that require high-speed computation and real-time processing. This can result in slow and sluggish user experiences. But focusing on the performance of a code that is not readable is useless. Moreover it can also be prone to bugs and errors. Performance is a quirky thing. Starting to write a code with performance as the first priority is not a path that any developer would take, or even recommend. In a Reddit thread, a developer gives an example of a code that compiles in 1 millisecond, and the other code in 0.1 millisecond. No one can really notice the difference between both the models as long as the code is “fast enough”. So improving the performance and focusing on it, while sacrificing the readability of the code can be counterproductive. Moreover, in the same Reddit thread, another developer pointed out that writing faster algorithms actually requires you to write harder code oftentimes, which again sacrifices the readability. 

LockBit Group Goes From Denial to Bargaining Over Royal Mail

LockBit's about-face - "it wasn't us" to "it was us" - is a reminder that ransomware groups will continue to lie, cheat and steal, so long as they can profit at a victim's expense. Isn't hitting a piece of Britain's critical national infrastructure - as in, the national postal service - risky? After DarkSide hit Colonial Pipeline in the United States in May 2021, for example, the group first blamed an affiliate before shutting down its operations and later rebooting under a different name. While hitting CNI might seem like playing with fire, many security experts' consensus is that ransomware groups' target selection remains opportunistic. Both operators and any affiliates who use their malware, as well as the initial access brokers from whom they often buy ready-made access to victims' networks, seem to snare whoever they can catch and then perhaps prioritize victims based on size and industry. What's notable isn't necessarily that LockBit - or one of its affiliates - hit Royal Mail, but that it decided to press the attack. 

Quote for the day:

“None of us can afford to play small anymore. The time to step up and lead is now.” -- Claudio Toyama

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