Banks aren’t as stupid as enterprise AI and fintech entrepreneurs think
First, banks have something most technologists don’t have enough of: Banks
have domain expertise. Technologists tend to discount the exchange value of
domain knowledge. And that’s a mistake. So much abstract technology, without
critical discussion, deep product management alignment and crisp, clear and
business-usefulness, makes too much technology abstract from the material
value it seeks to create. Second, banks are not reluctant to buy because they
don’t value enterprise artificial intelligence and other fintech. They’re
reluctant because they value it too much. They know enterprise AI gives a
competitive edge, so why should they get it from the same platform everyone
else is attached to, drawing from the same data lake? Competitiveness,
differentiation, alpha, risk transparency and operational productivity will be
defined by how highly productive, high-performance cognitive tools are
deployed at scale in the incredibly near future. The combination of NLP, ML,
AI and cloud will accelerate competitive ideation in order of magnitude. The
question is, how do you own the key elements of competitiveness? It’s a tough
question for many enterprises to answer.
Artificial Intelligence (AI) strategy: 3 tips for crafting yours
AI can drive value only if it is applied to a well-defined business problem,
and you’ll only know if you’ve hit the mark if you precisely define what
success looks like. Depending on the business objective, AI will commonly
target profitability, customer experience, or efficiency. Automation from AI
can yield cost savings or costs that are redirected to other uses. ... Treat
your data as a treasured asset. While data quality and merging disparate data
sources are common challenges, one of the biggest challenges in data
integration initiatives is streamlining, if not automating, the process of
turning data into actionable insights. ... If you are looking to develop AI
capabilities in-house, keep in mind that AI teams can benefit from having a
balance of skillsets. For example, deep expertise in modeling is critical for
thorough research and solution development. Data engineering skills are
essential in order to execute the solution. Your AI teams also need leaders
who understand the technology, at least enough to know what is and is not
possible. In running an AI team, it is important to create an environment that
fosters creativity but provides structure. Keep the AI team connected to
business leaders in the organization to ensure that AI is being applied to
high-priority, high-value use cases that are properly framed.
How special relativity can help AI predict the future
Researchers have tried various ways to help computers predict what might
happen next. Existing approaches train a machine-learning model frame by frame
to spot patterns in sequences of actions. Show the AI a few frames of a train
pulling out of a station and then ask it to generate the next few frames in
the sequence, for example. AIs can do a good job of predicting a few frames
into the future, but the accuracy falls off sharply after five or 10 frames,
says Athanasios Vlontzos at Imperial College London. Because the AI uses
preceding frames to generate the next one in the sequence, small mistakes made
early on—a few glitchy pixels, say—get compounded into larger errors as the
sequence progresses. Vlontzos and his colleagues wanted to try a different
approach. Instead of getting an AI to learn to predict a specific sequence of
future frames by watching millions of video clips, they allowed it to generate
a whole range of frames that were roughly similar to the preceding ones and
then pick those that were most likely to come next. The AI can make guesses
about the future without having to learn anything about the progression of
time, says Vlontzos.
TypeScript's co-creator speaks out on TypeScript 4.0
TypeScript was one of several efforts inside and outside Microsoft in those
few years to try and tackle this need -- first for large companies like
Microsoft and Google, but ultimately for the broader industry that was all
moving in the same direction. Other options, like Google Dart, tried to
replace JavaScript, but this proved to present too large a compatibility gap
with the web as it was and is. TypeScript, by being a superset of JavaScript,
was compatible with the real web, and yet also provided the tooling and
scalability that were needed for the large and complex web applications of the
early 2010s. Today, that scale and complexity is now commonplace, and is the
standard of any SaaS company or internal enterprise LOB [line of business]
application. And TypeScript plays the same role today, just for a much larger
segment of the market. ... TypeScript's biggest contribution has been in
bringing amazing developer tools and IDE experiences to the JavaScript
ecosystem. By bringing types to JavaScript, so many error-checking, IDE
tooling, API documentation and other developer productivity benefits light up.
It's the experience with these developer productivity benefits that has driven
hundreds of thousands of developers to use TypeScript.
Enabling transformation: How can security teams shift their perception?
There are clear opportunities to deliver this transformation through the
adoption of a unified security approach. By this, we mean the integration,
rationalisation and centralisation of security environments into a holistic
ecosystem. Adopting such an approach can help improve the operator experience
and make things simpler for the teams charged with maintenance – while also
providing a cure to the headaches caused by platform proliferation. Not only
this, but a unified security approach is a key enabler in helping security
leaders engage at the board level by delivering cost transformation. An
integrated security environment will serve to streamline operations for
security teams, allowing staff to focus on higher value tasks while automating
repetitive processes. In business terms, this means clawing back up to 155
days’ worth of effort for the average UK security team. Clearly, cost
reduction and operational efficiencies are central to demonstrating business
impact, but they should be viewed as a starting point rather than a security
teams’ entire value proposition.
Deep Learning Models for Multi-Output Regression
Neural network models also support multi-output regression and have the
benefit of learning a continuous function that can model a more graceful
relationship between changes in input and output. Multi-output regression can
be supported directly by neural networks simply by specifying the number of
target variables there are in the problem as the number of nodes in the output
layer. For example, a task that has three output variables will require a
neural network output layer with three nodes in the output layer, each with
the linear (default) activation function. We can demonstrate this using the
Keras deep learning library. We will define a multilayer perceptron (MLP)
model for the multi-output regression task defined in the previous section.
Each sample has 10 inputs and three outputs, therefore, the network requires
an input layer that expects 10 inputs specified via the “input_dim” argument
in the first hidden layer and three nodes in the output layer. We will use the
popular
ReLU
activation function in the hidden layer. The hidden layer has 20 nodes, which
were chosen after some trial and error. We will fit the model using mean
absolute error (MAE) loss and the Adam version of stochastic gradient descent.
Machine learning wards off threats at TV studio Bunim Murray
While its name is probably little-known to most viewers, Bunim Murray is kind
of a big deal in TV. Founded in the late 1980s when two TV producers were
flung together to produce a so-called ‘unscripted soap opera’ for the MTV
network, the resulting show, The Real World, was instrumental in establishing
the reality TV genre. The new company went on to develop global hits including
Keeping Up With The Kardashians, Project Runway and The Simple Life. Bunim
Murray’s CTO Gabe Cortina arrived at the firm with the infamous 2014 hack on
Sony Pictures weighing on his mind. This incident centred on the release of
The Interview, a comedy starring Seth Rogen and James Franco which depicted
the fictionalised assassination of North Korean dictator Kim Jong-Un. Likely
perpetrated by groups with links to the North Korean state, the large-scale
leak of data from the studio caused great embarrassment for many high-profile
individuals. From the get-go, Cortina understood that a similar kind of breach
could be seriously damaging to Bunim Murray. “We’ve been in business for 30
years. We have a strong brand and we’re known for delivering high-quality
shows,” he tells Computer Weekly.
Security Concerns for Peripheral APIs on the Web
To ensure a relatively secure browsing experience, browsers sandbox websites -
providing only limited access to the rest of the computer and even other
websites that are open on different tabs/windows. What differentiates Web
Bluetooth/USB APIs to other Web APIs such as the MediaStream or Geolocation that
received wide adaptation from all browser vendors is the specificity which they
offer. When a user enters a website that uses the Geolocation API, the browser
shows a pop-up requesting permission to access the current position. While
approving this request can pose a security risk, the user makes a conscious
decision to provide his or her location to the website. At the same time, the
browser exposes a set of specific API calls (such as getCurrentPosition) that
does exactly that. On the other hand, Bluetooth and USB communication work on a
lower level, making it difficult to discern which actions are being performed by
the website. For example, Web Bluetooth communicating with a device happens
using the writeValue that accepts arbitrary data and can cause any number of
actions on the target device.
Regulated Blockchain: A New Dawn in Technological Advancement
What a regulated blockchain portends is that the impact the negative
statements from government officials and the media along with regulatory
uncertainties have been having on entrepreneurs, investors, the market, and
the industry at large, will be a thing of the past. One area where we have
started seeing the positive impact and transformation in technology is the
case of the digital currency. The internet was the precursor of cashless
policy and internet banking all of which greatly reduced the stress people had
to go through to conduct businesses. The Chinese Government vehemently opposed
cryptocurrency because it was decentralized but it’s of great relief to see
that the People Bank of China (PBOC) is at the forefront of legitimizing
digital currency. As a part of a pilot program, PBOC introduced a homegrown
digital currency across four cities, this is a huge leap towards actualizing
the first electronic payment system by a major central bank. The Bank of
England (BoE) is also toeing the footsteps of China but at a review stage as
of July 2020. Andrew Bailey, the Governor of BoE was reported to have said, “I
think in a few years, we will be heading toward some sort of digital
currency.”
It’s never the data breach -- it’s always the cover-up
This is a warning to CSOs and CISOs: Remove all sense of impropriety in IR.
Concealing a data breach is illegal. Every decision made during an incident
might be used in litigation and will be scrutinized by investigators. In this
case, it's also led to criminal charges filed against a well-known security
leader. If your actions seem to conceal rather than investigate and resolve a
data breach, expect consequences. Neither the ransom nor the bug bounty are at
issue here. Paying the ransom through the bug bounty was alleged to help
conceal the breach. Firms should develop a digital extortion policy, so that
there are no allegations of impropriety should they choose to pay a ransom. In
addition, the guidelines of your bug bounty program should not be altered on
the fly to facilitate non-bug bounty program activities. Work closely
and openly with senior leadership on breaches and issues of ransom. Sullivan
tried to get the hackers to sign non-disclosure agreements -- a legal document
between two legitimate entities effectively acknowledging the hackers as
business entities -- which allowed Uber to treat the hackers as third parties.
Treating the ransom as a "cost of doing business" helped them conceal the
payment from the management team as well.
Quote for the day:
"What I've really learned over time is that optimism is a very, very important part of leadership." -- Bob Iger
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