Why Is There A Shortage Of MLOps Engineers?
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MLOps and DevOps engineers require different skill sets. Firstly, developing
machine learning models do not need a software engineering background as the
focus is mainly on the proof of concept/prototyping. Secondly, MLOps are more
experimental in nature compared to DevOps. MLOps calls for tracking different
experiments, feature engineering steps, model parameters, metrics, etc. MLOps is
not limited to unit testing. Various parameters need to be considered, including
data checks, model drift, analysing model performance, etc. Deploying machine
learning models is easier said than done as it involves various steps, including
data processing, feature engineering, model training, model registry and model
deployment. Lastly, MLOps engineers are expected to track data distribution with
time to ensure the production environment is consistent with the data it is
being trained on. Last year, AI/ML research hit the doldrums in the wake of the
pandemic; tech giants like Google slowed down hiring AI researchers and ML
engineers, and Uber laid off their AI research and engineering team.
AI security risk assessment using Counterfit
The tool comes preloaded with published attack algorithms that can be used to
bootstrap red team operations to evade and steal AI models. Since attacking AI
systems also involves elements of traditional exploitation, security
professionals can use the target interface and built-in cmd2 scripting engine
to hook into Counterfit from existing offensive tools. Additionally, the
target interface can allow for granular control over network traffic. We
recommend using Counterfit alongside Adversarial ML Threat Matrix, which is an
ATT&CK style framework released by MITRE and Microsoft for security
analysts to orient to threats against AI systems. ... The tool can help scan
AI models using published attack algorithms. Security professionals can use
the defaults, set random parameters, or customize them for broad vulnerability
coverage of an AI model. Organizations with multiple models in their AI system
can use Counterfit’s built-in automation to scan at scale. Optionally,
Counterfit enables organizations to scan AI systems with relevant attacks any
number of times to create baselines. Running this system regularly, as
vulnerabilities are addressed, also helps to measure ongoing progress toward
securing AI systems.
New Attacks Slaughter All Spectre Defenses
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The findings are going to obliterate a pile of work done by those who’ve been
working hard to fix Spectre, the team says. “Since Spectre was discovered, the
world’s most talented computer scientists from industry and academia have
worked on software patches and hardware defenses, confident they’ve been able
to protect the most vulnerable points in the speculative execution process
without slowing down computing speeds too much. They will have to go back to
the drawing board,” according to UVA’s writeup. The new lines of attack
demolish current defenses because they only protect the processor in a later
stage of speculative execution. The team was led by UVA Engineering Assistant
Professor of Computer Science Ashish Venkat, who picked apart Intel’s
suggested defense against Spectre, which is called LFENCE. That defense tucks
sensitive code into a waiting area until the security checks are executed, and
only then is the sensitive code allowed to execute, he explained. “But it
turns out the walls of this waiting area have ears, which our attack exploits.
We show how an attacker can smuggle secrets through the micro-op cache by
using it as a covert channel.”
Drake: Model-based design in the age of robotics and machine learning
The Drake developers have a philosophy of rigorous test-driven development.
The governing equations for multibody physics are well known, but there are
often bugs in a complex engine like this. If you scan the codebase, you will
find unit tests that contain comparisons with closed-form solutions for
nontrivial mechanics problems like a tumbling satellite, countless checks on
energy conservation, and many other checks that help the rest of the team
focus on manipulation with the confidence that the multibody models are
implemented correctly. Importantly, this dynamics engine is not only for
simulation. It is also built for optimization and for control. The exact same
equations used for simulation can be used to compute forward or inverse
kinematics and Jacobians. They can also be used for more complex queries like
the gradient of an object’s center of mass. We provide smooth gradients for
optimization whenever they are available (even through contact). Drake also
supports symbolic computation, which is very useful for structured
optimization and for use cases like automatically extracting the famous
“lumped parameters” for parameter estimation directly from the physics
engine.
How to lead a digital transformation — ethically
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Not all ethical imperatives related to digital transformation are as debatable
as the suggestion that it should be people-first; some are much more black and
white, like the fact that you have to start somewhere to get anywhere.
Luckily, “somewhere” doesn’t have to be from scratch. Government, risk and
compliance (GRC) standards can be used to create a highly structured framework
that’s mostly closed to interpretation and provides a solid foundation for
building out and adopting digital solutions. The utility of GRC models applies
equally to startup multinationals and offers more than just a playbook;
thoughtful application of GRC standards can also help with leadership
evaluation, progress reports and risk analysis. Think of it like using bowling
bumpers — they won’t guarantee you roll a strike, but they’ll definitely keep
the ball out of the gutter. Of course, a given company might not know how to
create a GRC-based framework (just like most of us would be at a loss if
tasked with building a set of bowling bumpers). This is why many turn to
providers like IBM OpenPages, COBIT and ITIL for prefab foundations.
Use longitudinal learning to reduce risky user behavior
Longitudinal learning is a teaching method that is gaining traction within
academia, particularly for corporate training. This continuing education
approach involves administering shorter assessments of specific content (such
as whether to click on a URL embedded within an email sent by an unknown user)
repeatedly over time. Through a consistent assessment process, security
concepts and information are reinforced so that knowledge is retained and
accumulated gradually. Studies on longitudinal learning in healthcare showed
that testing medical students in combination with explaining the information
is the most effective way to drive the long-term retention of information.
Consistent, repetitive lessons are critical to help employees overcome the
cognitive biases that cybercriminals count on to execute their attacks. The
human mind is stingy; that is to say, that the brain processes so much
information daily that it is constantly trying to take shortcuts to save
energy and enable multi-tasking. Cybercriminals know this which is why
impersonation attacks, phishing, and rnalicious URLs are so effective. Did you
catch the typo in the last sentence? If not, look at the word “malicious”
again.
This ambitious Microsoft project aims to fix cloud computing security
A Microsoft research project, Project Freta, aims to change that, providing
tools to identify malware running on virtual machines in the cloud. It takes
an economic approach to managing malware, which is only valuable to bad actors
as long as it's undetected: once identified on one system, malware code is no
longer reusable, as its signature can be added to active scanning tools. But
if we're to have any success, we need to be able to scan many thousands of
devices, at a push of a button. The very industrial scale of the cloud means
that traditional scanning techniques are too slow, looking for one or two
compromised images in an ever-growing fleet. It's a reminder of that old Cold
War adage: your attackers only have to be lucky once, you have to be lucky
every time. Microsoft Research's security specialists have been thinking about
this problem, and Project Freta encapsulates much of this thinking in a
cloud-centric proof-of-concept. Designed to look for in-memory malware, it
provides a portal where you can scan memory snapshots from Linux and Windows
virtual machines. Initially focusing on virtual machine instances, it's
intended to show the techniques and tools that can be used to scan for malware
at massive scale.
Why India Is A Hotspot For Data Labelling Services?
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“Numerous data labelling firms have sprung up to address this growing need,
and many of them are tapping into a global pool of ‘gig workers’ that can get
this done effectively. Software and algorithms make it easier to divvy up
tasks and have people work at their convenience. India offers a huge talent
pool with ready access to smartphones and the ability to tap into a new income
source or to supplement their earnings. Time difference, in this case, can
even be an asset,” said Girish Muckai, Chief Sales & Marketing Officer of
HEAL Software Inc. “Training AI models to deliver high levels of accuracy is
critical to success. However, labelling training data sets is tedious work.
It’s time consuming, complex and requires significant workforce. The tech
industry’s outsourcing boom in India and its large population, make it a
growing hotbed of this precision work. Its people and skills position India as
a key resource for years to come in an increasingly digital world,” said Lori
McKellar, Senior Director, Product Marketing at OpenText. “India has emerged
as a huge pool of employable workers to undertake data labelling jobs.
Lessons I've Learned From My Career in Technology
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One of the things that I wish I had known earlier in my career is that finding
your passion is the most crucial part of the job. Don't misunderstand me --
finding your passion doesn't mean that you'll be doing what you love every
day. It's about finding a company, industry, or role that you believe can make
a difference. Working in IT is challenging. You'll have hard deadlines to
meet, clients to impress, customers to help -- and working nights, weekends
and holidays are all an inevitability in most jobs. However, the thing that
will push you through it and make it all worthwhile is if you're passionate
about the work you do. How can you tell if you're passionate about a company
or an industry? You get excited thinking about what the business or industry
does. This is so important. If you're not excited about the potential impact
of your work, you're not passionate about the industry. This passion will help
to drive you through the more monotonous parts of your job. You're helping
your customers: So many IT companies are now inventing problems to solve with
their products instead of focusing on the issues consumers face. Look for a
job that sees you actively helping consumers -- this will give you a sense of
accomplishment at the end of the day.
The Rise of Asynchronous Collaboration and What It Means for Development Teams
Asynchronous collaboration and project management tools can serve as our
panacea, an escape from the virtual spotlight and constant time-suck of video
chats and conference calls. These tools offer us a respite by providing a
means to collaborate very effectively through cards and boards filled with
status updates, comments, files, and even visual workflows that can take the
place (and, in some cases, improve upon) our beloved whiteboards. They can
effectively take the place of non-productive meetings, allowing us to track
our work, collaborate with our teammates, and achieve our objectives without
the need for lights and cameras. Here, I’ll share information about some of
the asynchronous collaboration and project management tools I find most useful
and how they’ve helped us maximize productivity and collaboration. I must
begin, though, with a couple of caveats. First, while the tools I’ll reference
here are, on the whole, great, there are some drawbacks to asynchronous
collaboration that you should be aware of, and I’ll go into detail about them
a little further on. Second, these tools cannot and should not be considered
permanent replacements for video calls.
Quote for the day:
"Brilliant strategy is the best route
to desirable ends with available means." -- Max McKeown
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