How AI is changing scientific discovery
While the spread of misinformation is one of the many ways that AI is changing
science, an even broader and more positive application of this technology is
self-driving labs (SDL). In an SDL, AI selects new material formulations aided
by robotic arms to synthesise new materials. While this technology is currently
limited to discovering new materials, it relieves researchers of having to
grapple with trillions of possible formulations. This greatly improves the
labour productivity in science, saving time and money and allowing researchers
more time to improve creative aspects such as experimental design. In fact, in
April 2023, UofT was awarded Canada’s largest-ever research grant of $200
million in research funding towards Acceleration Consortium—a UofT-based network
that aims to accelerate materials discovery through AI and robotics. Through
this funding, autonomous labs are being built at UofT, such as in the Leslie Dan
Faculty of Pharmacy where AI, automation, and advanced computing are used to
iteratively test and develop material combinations for new drug formulations.
Need for upskilling and cross-skilling amongst cybersecurity professionals
The urgency of upskilling and cross-skilling is further underscored by the
shortage of skilled cybersecurity professionals. In the post-pandemic years,
the digital transformation across industries has resulted in a massive demand
for cybersecurity professionals with the right skills. As per estimates, there
are over 5.4 million cybersecurity professionals currently globally, and there
are nearly 4 million job openings in the field. In fact, 67% of cybersecurity
professionals have reported that their organizations face a shortage of
adequately skilled personnel to secure their digital infrastructure. Even in
India, where digital infrastructure has grown by leaps and bounds in the last
two years, there is a major need to train more people on cutting-edge
cybersecurity practices. As organizations struggle to fill critical
cybersecurity roles, existing professionals must take the initiative to expand
their skill sets. Training programs, certifications, and continuous learning
opportunities can empower cybersecurity experts to bridge the gap between
their current knowledge and the ever-evolving threat landscape.
Data Sovereignty and Digital Governance in APAC: What’s Next?
There is increasing diversity of data sources, datasets, workloads and the
permeance of cloud and multi-cloud, and edge computing throughout the data
management cycle. This coupled with more interconnected and decentralised
organisations with embedded solutions and loosely coupled architectures has
necessitated breaking down data silos while maintaining data and metadata
quality. This hence can result in breaking down of geopolitical borders, due
to the fact that data can get generated, processed, localised, stored,
transferred, transformed and accessed across different countries. This
necessitates knowledge and compliance to privacy and security laws of all
applicable countries, especially in the cloud, edge, co-location
infrastructure and on-premise ecosystems. Moreover, there are potentially
complex situations and conflicts especially in case of variances in Data
Protection Acts across countries such as data flows between EU-GDPR and the US
Privacy laws. There could be additional different scenarios at federal or
state levels. Similar considerations must be planned and executed in case of
cross-border data flows, backup and disaster recovery.
Boards of directors: The final cybersecurity defense for industrials
First and foremost, board members provide oversight and guidance. They should
ensure that executives and their teams set a high standard for cybersecurity.
They should then follow through on achieving them by ensuring that security is
embedded by design in digital products and that technology teams share
responsibility for cybersecurity. The board is the last line of defense in
ensuring such initiatives get planned and funded. Boards also look at risk
prioritization and trade-offs. They are often intimidated when it comes to
determining risk levels and giving fact-based inputs into risk trade-offs. In
addition, the vocabulary and reporting capabilities used by security teams with
their boards are often inconsistent and technical. As a result, it can be
overwhelming for board members who want to contribute meaningfully to reducing
cybersecurity risk but are not quite sure how. A board member does not need to
have specific knowledge about cybersecurity to add value. Instead, they need to
test and ask the cyber team about potential business impacts. This means the
cyber team should equate cyber issues and controls with business risks.
Compliance meets AI: A banking love story
Most financial institutions are at preliminary stages in evaluating
opportunities to use generative AI in their operations. Some of the areas where
we are seeing the anticipated use of LLMs are in customer services. Large
language models can interact with a bank’s customers in very natural
conversations. Depending on the data that the bank trains the LLM on, the chat
bots can answer questions about customer accounts and even provide recommended
product offerings and investment advice. Several large banks are working with
internal LLM models to capture call center notes, organize information for
investment advisors and organize other product data for customer service reps,
with plans to roll out to more customer-facing uses as extensive testing
addresses potential risks. Banks are also assessing opportunities to improve
internal operations. Generative AI capabilities enable new ways to analyze data.
One practical use case for most organizations is to train LLMs on all the
pockets of organizational information that employees need to access to do their
jobs.
Navigating fraud and AML challenges with innovation solutions in a new financial frontier
In the intricate domain of Anti-Money Laundering (AML) compliance, the quality
of data plays a pivotal role. Wolters Kluwer’s CCH iFirm AML module underscores
this by ensuring access to leading credit bureaus and governmental data sets.
The accuracy, completeness, timeliness, consistency, and relevance of data are
fundamental to the effective detection, prevention, and reporting of potential
money laundering activities. High-quality data not only aids in identifying
suspicious transactions more accurately but also enhances the efficiency of the
compliance process. For CFOs, this means a significant reduction in the risk of
non-compliance penalties and the fostering of trust with regulatory bodies. ...
The advent of AI-boosted cyber threats poses a significant challenge for CFOs in
2024. Darktrace’s study reveals a stark reality: while 89% of IT security
specialists anticipate these threats will significantly impact their
organisations within the next two years, 60% admit to being ill-prepared to
defend against them. The escalation in sophisticated phishing attacks,
leveraging advanced language and punctuation, underscores the evolving nature of
cyber threats.
Prompt Injection Vulnerability in Google Gemini Allows for Direct Content Manipulation
The researchers say that the prompt injection attacks impact Gemini Advanced
accessed by users with Google Workspace, and organizations that are making use
of the Gemini API. The content manipulation risk is also said to more generally
apply to world governments as it could be used to output inaccurate or falsified
information about elections. The risk is particularly acute as Google Gemini has
been trained on audio, video, images and code in addition to text. One of the
central issues identified by the researchers is that it is relatively trivial to
get Google Gemini to leak system prompt information. This is information about
the “prime directives” of the AI model, so to speak, that should not be visible
to service users. The researchers’ first prompt injection attack is to simply
change the wording when asking the AI about this information, causing it to spit
out its core rules when asked about its “foundational instructions” instead.
Another exploit involving the system prompt is a seeming state of confusion that
the AI can be thrown into by peppering it with many uncommon tokens.
RegTech solutions can be a game changer in fintech regulatory scrutiny
RegTech solutions allow businesses to create transparency and accountability
within compliance procedures and ensure the timely conclusion of statutory
obligations. Employers can stay on top of important changes and address them
promptly with the help of compliance management software. Digital, authentic,
and tamper-proof copies of all required compliance papers are stored
conveniently. While onboarding any RegTech solution, the legal teams of the
RegTech players conduct comprehensive compliance applicability assessments to
identify the list of applicable acts and compliances. This helps in creating a
list relevant to each financial institution. RBI directives work to
continuously evolve the regulatory landscape to keep up with innovations in
technology and services. ... The RegTech space has been investing heavily in
creating automation layers for compliance document generation and integration
with the transaction systems to eliminate any manual touch points. Additionally,
they are preparing themselves for API based filings as soon as the regulators
are ready to adopt a GST like model and create an eco-system for RegTech
players.
Managing Technical Debt in Agile Environments
Usually, Technical debt occurs when teams rush to push new features within
deadlines, by writing code without thinking about other considerations such as
security, extensibility, etc. Over time, the tech debt increases and becomes
difficult to manage. ... Code Debt: When we talk about tech debt, code debt is
the first thing that comes to mind. It is due to bad coding practices, not
following proper coding standards, insufficient code documentation, etc. This
type of debt causes problems in terms of maintainability, extensibility,
security, etc. Testing Debt: This occurs when the entire testing strategy is
inadequate, which includes the absence of unit tests, integration tests, and
adequate test coverage. This kind of debt causes us to lose confidence in
pushing new code changes and increases the risk of defects and bugs surfacing in
production, potentially leading to system failures and customer dissatisfaction.
Documentation Debt: This manifests when documentation is either insufficient or
outdated. It poses challenges for both new and existing team members in
comprehending the system and the rationale behind certain decisions, thereby
impeding efficiency in maintenance and development efforts.
Science Simplified: What Is Quantum Mechanics?
In a more general sense, the word “quantum” can refer to the smallest possible
amount of something. The field of quantum mechanics deals with the most
fundamental bits of matter, energy and light and the ways they interact with
each other to make up the world. Unlike the way in which we usually think about
the world, where we imagine things to have particle- or wave-like properties
separately (baseballs and ocean waves, for example), such notions don’t work in
quantum mechanics. Depending on the situation, scientists may observe the same
quantum object as being particle-like or wave-like. For example, light cannot be
thought of as only a photon (a light particle) or only a light wave, because we
might observe both sorts of behaviors in different experiments. Day to day, we
see things in one “state” at a time: here or there, moving or still, right-side
up or upside down. The state of an object in quantum mechanics isn’t always so
straightforward. For example, before we look to determine the locations of a set
of quantum objects, they can exist in what’s called a superposition — or a
special type of combination — of one or more locations.
Quote for the day:
"Success comes from knowing that you
did your best to become the best that you are capable of becoming." --
John Wooden
