How healthcare IT can be kept smart
As with many industries, the healthcare sector has seen a rapid phase of
digitalisation, with new connected medical devices intertwining patient
treatment with IT infrastructure that was traditionally separate from day to
day healthcare practice. There can be no doubt this has boosted efficiencies
and had a positive impact on patient care. However, digitalisation comes with
a catch. With so many new connected devices, today’s hospital IT networks have
more potential points of failure than ever before. As with any information
system, the storage and transfer of data is at the heart of all healthcare IT
systems. Most if not all medical IoT devices rely on data and information
being readily available through various points in the hospital network. For
example, a radiologist will routinely require access to patient imaging
records in order to review scans that have been automatically uploaded to the
system by an MRI machine. To facilitate this degree of connectivity, most
hospitals have what is called an integration engine. This is a central IT
communications hub that securely stores and distributes information and data
where and when it is needed. Think of the integration engine as the hospital’s
central nervous system, facilitating all communications across the network.
Why Innovation Takes More Than Genius
It’s easy to look at someone like Steve Jobs or Elon Musk and imagine that
their success was inevitable. Their accomplishments are so out of the ordinary
that it just seems impossible that they could have ever been anything other
than successful. You get the sense that whatever obstacles they encountered,
they would overcome. Yet it isn’t that hard to imagine a different path. If,
for example, Jobs had remained in Homs, Syria, where he was conceived, it’s
hard to see how he would have ever been able to become a technology
entrepreneur at all, much less a global icon. If Apartheid never ended, Musk’s
path to Silicon Valley would be much less likely as well. The truth is that
genius can be exceptionally fragile. Making a breakthrough takes more than
talent. It requires a mixture of talent, luck and an ecosystem of support to
mold an idea into something transformative. In fact, in my research of great
innovators what’s amazed me the most is how often they almost drifted into
obscurity. Who knows how many we have lost? On a January morning in 1913, the
eminent mathematician G.H. Hardy opened his mail to find a letter written in
almost indecipherable scrawl from a destitute young man in India named
Srinivasa Ramanujan.
Systems integrators are evolving from tech experts to business strategists
Nigel Fenwick, vice president and principal analyst at Forrester, said that
systems integrators (SIs) have been investing in emerging technologies and
developing software to accelerate time to value for clients. "There's
demand in IT transformations for SIs and service providers to help clients
architect their technology so that the business can evolve with new
technologies even faster," he said. "Modern system architectures make it
easier for services firms to connect systems through APIs and microservices
than it used to be." Adya shared a project Infosys completed with a large
retailer as one example of this orchestration approach. The client wanted to
solve an employee experience problem focused on accessing personal data such
as salary information, leave time, and bonus information. Each type of
information lived in its own silo, requiring multiple log-ins and creating an
unpleasant experience. Infosys combined multiple data sets into a single
interface that employees and temp workers access by typing in an employee
number. "This solved an experience problem that involved integrating the
back end and the front end and building a platform," he said.
A Robust Cybersecurity Policy is Need of the Hour: Experts
“There has been a recent surge in cyberattacks on Indian digitalscape that are
only increasing in scope and sophistication, targeting sensitive personal and
business data and critical information infrastructure, with an impact on
national economy and security. ... And while formulation and adoption of
policies might still take time, this is a clarion call to the Indian internet
users to pay attention to the threats, on creating robust ‘firewalls’, and
conducting regular cybersecurity and data protection audits.” – Nikhil
Korgaonkar, regional director, India and SAARC, Arcserve “With cyberattacks
increasingly becoming sophisticated, cybersecurity and digitization cannot and
should not exist in silos. What we need now is a robust cybersecurity roadmap
that will address the gaps and provide us a strong cyber-armor. Covid-19
situation has only accelerated the pace of digitization, potentially
amplifying these security concerns. It is time for businesses to take
advantage of approaches like micro-segmentation, encryption and dynamic
isolation, enhanced by the power of emerging technologies like AI and ML to up
their cybersecurity game.” – Sumed Marwaha, regional services vice president
and managing director, Unisys India
3 Huge Ways Companies Are Delighting Customers With Artificial-Intelligence-Driven Services
Driven by the likes of Netflix, this notion of customization and
personalization is a major business trend. If your customers don’t already
expect a more intelligent, personalized service offering, they soon will do.
If you aren’t able to offer such a service, rest assured your competitors
will. (And, increasingly, that competition may come from the tech sector
itself. Consider the rise of personal finance apps that are seriously
challenging traditional banking service providers.) We tend to think of retail
as a product-based industry, but in fact, it perfectly illustrates this move
towards more personalized services. Amazon was an early pioneer of
data-driven, personalized shopping recommendations, but now a wave of new
services has sprung up to offer a similarly tailored approach for consumers.
Stitch Fix, which delivers hand-picked clothing to your door, is a great
example. With Stitch Fix, you detail your size, style preferences, and
lifestyle in a questionnaire. Then, using AI, the system pre-selects clothes
that will fit and suit you, and a (human) personal stylist chooses the best
options from that pre-selected list. And voila, the perfect clothes for you
arrive at your door every month.
Easy Interpretation of a Logistic Regression Model with Delta-p Statistics
Imagine a situation where a credit customer applies for a credit, the bank
collects data about the customer - demographics, existing funds, and so on -
and predicts the credit-worthiness of the customer with a machine learning
model. The customer’s credit application is rejected, but the banker doesn’t
know why exactly. Or, a bank wants to advertise their credits, and the target
group should be those who eventually can get a credit. But who are they? In
these kinds of situations, we would prefer a model that is easy to interpret,
such as the logistic regression model. The Delta-p statistics makes the
interpretation of the coefficients even easier. With Delta-p statistics at
hand, the banker doesn’t need a data scientist to be able to inform the
customer, for example, that the credit application was rejected, because all
applicants who apply credit for education purposes have a very low chance of
getting a credit. The decision is justified, the customer is not personally
hurt, and he or she might come back in a few years to apply for a mortgage.
Shifting Left: The Evolving Role of Automation in DevOps Tools
Advanced automation tools eliminate the manual and time-consuming
configuration per project within DevOps, thereby removing the friction between
developers and DevOps teams when needing to add scanning steps into the jobs
of all CI pipelines. Adding jobs or steps to scan code is challenging using
the traditional CI-scan model. Advanced automation tools ultimately break down
barriers between teams and allow them to play better together and achieve true
DevSecOps integration. At the end of the day, shifting left and automating
your CI/CD pipeline will dramatically improve the integration of security
within the SDLC. Organizations can instantly onboard their development,
security, and operations teams and simplify the governance of their security
policies and DevSecOps processes. The traditional AST solution providers are
leaving developers behind because without the ability to scan source code
directly in your environment, you’re left having to manually process scans —
leaving a lot of room for marginal error and adding a lot of time to your
end-delivery date. If I can leave you with one thing, it’s that integration is
key to automation and the tools you use should enable the most shift left
approach possible, where automation can occur within the SDLC — changing the
way AST solutions are embedded within all DevOps environments.
GPT-3 Is an Amazing Research Tool. But OpenAI Isn’t Sharing the Code.
At its heart, GPT-3 is an incredibly powerful tool for writing in the English
language. The most important thing about GPT-3 is its size. GPT-3 learned to
produce writing by analyzing 45 terabytes of data, and that training process
reportedly cost millions of dollars in cloud computing. It has seen human
writing in billions of combinations. This is a key part of OpenAI’s long-term
strategy. The firm has been saying for years that when it comes to deep
learning algorithms, the bigger the better. More data and more computing power
make a more capable algorithm. For instance, when OpenAI crushed professional
esports players at Dota 2, it was due to its ability to train algorithms on
hundreds of GPUs at the same time. It’s something OpenAI leaders have told me
previously: Jack Clark, policy director for OpenAI, said that the bigger the
algorithm, the “more coherent, more creative, and more reliable” it is. When
talking about the amount of training the Dota 2 bots needed, CTO Greg Brockman
said, “We just kept waiting for the magic to run out. We kept waiting to hit a
wall, and we never seemed to hit a wall.” A similar approach was taken for
GPT-3.
Indian leaders say upskilling key cybersecurity challenge: Microsoft
The pandemic had direct implications on cybersecurity budgets and staffing,
with 33 per cent business leaders in India reporting a 25 per cent budget
increase for security. More than half (54 per cent) of the leaders in the
country said that they would hire additional security professionals in their
security team. “A vast majority (70 per cent) of leaders in India stated that
they plan to speed up deployment of Zero Trust capabilities to reduce risk
exposure,” the findings showed. Globally, 90 per cent of businesses have been
impacted by phishing attacks with 28 per cent admitted to being successfully
phished. Notably successful phishing attacks were reported in significantly
higher numbers from organizations that described their resources as mostly
on-premise (36 per cent) as opposed to being more cloud-based. In response to
Covid-19, more than 80 per cent of companies added security jobs. While 58 per
cent of companies reported an increase in security budgets globally, 65 per
cent reported an increase in compliance budgets. “The shift to remote work is
fundamentally changing security architecture,” said the survey.
How to manage your edge infrastructure and devices
“Firstly, lack of external network connectivity to a device making it necessary
to process data at the edge. Typically, this has been due to difficult
environments or security requirements. Secondly, a need for speed that prevents
sending data through a network due to latency, where moving the data costs more
in terms of time than having the processing power of a data centre or the cloud
available. “This is absolutely true for certain use cases. On the factory floor,
for example, there is a desire to prevent network connectivity from bringing an
entire plant down. In fact, in many factories, the level of bandwidth currently
available can often be too low to have all equipment sending data back to the
data centre. In this case, it is critical to place analytics tools at the edge
with no disruption, sitting the algorithm next to the hardware. “However, for
businesses with non-critical use cases, this is changing. Over time, the drivers
behind the need for edge analytics have changed as network speed and
connectivity become faster and more prevalent. As such, the roundtrip of data to
the network – which is going faster every day – will not hinder digital progress
and thus businesses are increasingly happy to manage infrastructure and devices
in this way.”
Quote for the day:
“I’m convinced that about half of what separates successful entrepreneurs from non-successful ones is pure perseverance.” -- Steve Jobs
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