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Fintech bytes podcast: How to leverage FinTechs through digitalisation


Tags fintech blockchain how-to

A podcast episode featuring Tony Clark, CEO of NextWave Consulting, discussing the significance of digitalisation in fintech. By Maya Kokerov. In the podcast’s 20th episode, NextWave Consulting Founder and CEO Tony Clark is interviewed by Reeve Boyd, an associate in CMS’s Finance Disputes team. Tony and Reeve delve into the significance of digitalisation in driving strategic competitive advantage for fintech companies. They also provide a detailed guide on the steps to take to succeed in a constantly evolving digital landscape.

Here are the key points:

  • Digitalisation for Competitive Advantage: Tony Clark emphasizes the importance of digitalisation in driving strategic competitive advantage for fintech companies
  • NextWave’s Role: NextWave helps financial institutions modernise through technology, focusing on automation, AI, and data
  • SPEED Framework: The framework includes Strategy, Platforms, Ecosystems, Engagement, and Data, guiding firms in their digital transformation
  • Challenges and Opportunities: The discussion covers the opportunities and risks of digitalisation, including regulation, operational resilience, and ethical AI

For financial institutions, the rule book is evolving and it’s crucial to play by the new digital rules while keeping a close eye on regulation. Nice one!

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CSS length units


Tags app-development css web-development frontend

A comprehensive guide covering nine types of lengths that CSS uses to size elements in terms of dimensions, space, time, and even sound. By Geoff Graham.

Many CSS properties accept numbers as values. Sometimes those are whole numbers. Sometimes they’re decimals and fractions. Other times, they’re percentages. Whatever they are, the unit that follows a number determines the number’s computed length. And by “length” we mean any sort of distance that can be described as a number, such as the physical dimensions of an element, a measure of time, geometric angles… all kinds of things!

The article then explains:

  • Types of numbers
  • Absolute units
  • Relative units
  • What about unit-less numbers?
  • We can create our own custom units!
  • When to use one unit over another
  • Use container units for responsive design, where possible

In some cases, we may want to work with a numeric value, but CSS doesn’t exactly recognize it as one. In these cases, the number is recognized as a “string” value instead, regardless of whether or not it contains alphabetical characters. That’s where we can use @property to create what’s called a “custom property” that evaluates a numeric value in a certain way.

Container queries in general are so gosh-darn great for responsive layouts because they look at the size of the container and let us apply styles to its descendants when the container is a certain size. Super interesting read!

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How to use AI in DevOps


Tags ai data-science cio devops

Did you miss a critical bug? Spent hours troubleshooting a failed deployment? DevOps professionals have been there more often than they’d like.AI in DevOps offers a powerful solution. It’s not a magic bullet, but by integrating machine learning and intelligent automation, you can streamline your workflow, identify potential issues early on, and make data-driven decisions. By @clickup.com.

This article explores how AI can transform your DevOps practices, making software building and management more efficient and reliable, including:

  • Understanding AI in DevOps
  • Benefits of using AI in DevOps
  • How to use AI for DevOps in CI/CD
    • Intelligent code analysis
    • Predictive testing
    • Self-healing deployments
    • Proactive monitoring and alerting
    • Resource optimization and cost management
    • Enhanced collaboration and communication
  • Using AI software for DevOps
    • Build a live knowledge base: Information at your fingertips
    • Automate documentation: Ditch the tedious tasks
    • Level up communication: Write with clarity
    • Personalized communication: Reports tailored for each audience
  • Managing DevOps Teams with innovative tools

… and much more. DevOps teams, by their very nature, require a unique approach to project management that blends traditional project management principles with the collaborative and fast-paced world of DevOps. Nice one!

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Rapid progress in AI research and development faces hurdles


Tags ai analytics big-data cio

Major Chinese tech companies last week announced extensive price cuts for their large language model (LLM) products used for generative artificial intelligence, a move that experts say is tipped to speed up the application of AI models in the domestic market and in research. While price wars are not uncommon in the world of LLMs, this comes as Chinese developers continue to make progress in the commercialisation of AI technology in recent months. By Amber Wang.

Lin Yonghua, deputy director and chief engineer of the Beijing Academy of Artificial Intelligence (BAAI), a leading non-profit in AI research and development, said the “bottleneck” around training data is looming large.

The article then explains:

  • Need for localised models
  • Filling the data gap
  • The GPU bottleneck

Industry discussions also focus on the strong demand for computing power. Lack of computing power inhibits the implementation of LLMs and delays product deployment, they say. Good read!

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Qualcomm: Generative AI and impressive diversification signal a new era of growth


Tags infosec management ai cio machine-learning

QCOM’s entry into the AI chips market seems promising, with MSFT endorsing the ARM-based Snapdragon X Elite CPU chips as the “fastest, most AI-ready PC ever built.” By Juxtaposed Ideas.

MSFT has recently launched new AI-powered personal computers with QCOM, namely Copilot+ PCs, powered by the latter’s latest ARM-based Snapdragon X Elite CPU chips. With OpenAI’s multimodal GPT-4o model embedded on these PCs while supposedly boasting faster processing speeds and more efficient batteries than AAPL’s most advanced MacBook Air with the M3 processor, it is unsurprising that MSFT has touted these as the “fastest, most AI-ready PC ever built.”

For context, the Neural Processing Unit [NPU] is touted to be the key in enhancing AI performance in a PC, given that it simulates the “human brain’s neural network” in processing “large amounts of data in parallel, performing trillions of operations per second.” Interesting read!

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Shift left vs shift right: A DevOps mystery solved


Tags devops machine-learning tdd docker containers

Shift left and shift right are core testing concepts of the agile DevOps methodology, which speeds up application development by releasing small builds frequently as code evolves. As part of the continuous cycle of progressive delivery, DevOps teams are also adopting shift left and shift right principles to ensure software quality in these dynamic environments. By Saif Gunja.

The article then explains:

  • In DevOps, what is shift left? And what is shift right?
  • Why is shift left important?
  • What does shift right mean in DevOps?
  • Why shift right and shift left are critical for microservices architecture
  • Types of shift right tests
  • Types of shift left tests
  • The application security dividend of shift right and shift left

… and more. Shift right is the practice of performing testing, quality, and performance evaluation in production under real-world conditions. Shift right methods ensure that applications running in production can withstand real user load while ensuring the same high levels of quality. Nice one!

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Big data strategies


Tags analytics big-data app-development management cio how-to

Do I have “big data”? Oddly, this is not actually a straightforward question for two reasons. By @practicaldatascience.org.

As a result, the fact that you have 16GB of RAM doesn’t mean you can easily work with a 14GB file. As a general rule, you need at least two times as much memory as your file takes up when first loaded.

If you have big data, you basically have four options:

  • Use chunking to trim and thin out your data so it does fit in memory (this works if the data you were given is huge, but the final analysis dataset you want to work with is small)
  • Buy more memory. Seriously, consider it
  • Minimize the penalties of working off your hard drive (not usually practical for data science)
  • Break your job into pieces and distribute over multiple machines

If your program starts using more space than you have main memory, your operating system will usually just start using your hard drive for extra space without telling you (this is called “virtual memory”, and is nice in that it prevents your computer from crashing, though it will slow stuff down a lot). As a result, you won’t always get an error message if you try and load a file to is much bigger than main memory. More details on how do I check to see if my data is fitting in memory in the article. Interesting read!

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To end burnout, cybersecurity must tolerate failure


Tags infosec management web-development cio

At Gartner Security and Management Summit, speakers explained that you can’t buy your way out of cybersecurity burnout. They discussed how a shift from a protection-focused program to a response-focused security strategy can help. By Ijeoma S. Nwatu.

“It is hard simply to survive amid the complicated operating environment you have to defend,” Mixter began. “It gets even harder as budget growth starts to level off, and as the cybersecurity talent gap expands, both here in North America and all around the world. The talent shortage is a very real threat to companies and organizations worldwide. The number of cyber talent we need might as well be a billion for all that we’re going to solve in the near term.”

To kick off the 2024 Gartner Security & Risk Management Summit last week, Gartner’s vice president analysts, Christopher Mixter and Dennis Xu opened the three-day conference with an introduction to augmented cybersecurity with a focus on leaving the zero-tolerance-for-failure mindset behind.

62% of cybersecurity leaders have experienced burnout at least once in the past year,” Xu shared according to Gartner. “You all are doing good work, but you shouldn’t have to be heroes. Interesting read!

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Everything Apple Intelligence will do for you (so far)


Tags ai app-development big-data data-science robotics

While the arrangement between OpenAI and Apple is attracting a lot of attention, Apple has put together a sizable number of its own large language model (LLM) tools that will run on a compatible device or in its secure cloud, Private Cloud Compute. By Jonny Evans.

To achieve this, it draws on what your device knows about you and on-device intelligence, or, where necessary, in the cloud via the highly secure Private Cloud Compute system. At all times, Apple says it’s working to protect user privacy, which means your data is protected unless you choose to use a third-party AI, such as ChatGPT.

The article deals with:

  • Tools to help you write better
  • Mail is getting better
  • Meetings, now with AI assistants
  • Tools to help you stay focused
  • Making images
  • Photos gets better at helping you find your stuff
  • Wave your Image Wand
  • Siri gets serious attention

It is likely there will be additional features in place by the time Apple Intelligence is made available in the fall product software updates. This is because developers can use App Intents to make features available within their apps also available across the system. Meanwhile, developers get to use Xcode Complete to work smarter. Good one!

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Big data statistics 2023: How much data is in the world?


Tags fintech app-development big-data data-science miscellaneous

You’ve probably noticed that the term “big data” is frequently used these days. That’s because big data is a major player in the digital age. This term refers to complex and massive data sets that far exceed the potential of traditional data processing applications. By Ogi Djuraskovic.

The article explains stats about:

  • General overview of big data statistics and facts
    • There is 10% unique and 90 % replicated data in the global datasphere
    • Amount of data/information generated, gathered, copied, and consumed to reach 180 zettabytes by 2025
  • Overview of data analytics stats and facts
  • Corporate big data statistics and facts

    • Microsoft is the largest vendor in the worldwide big data and analytics software market with a 12.8% market share
  • Cloud computing and big data centers statistics

    • In 2021, the US is the country with the most data centers (2670) in the world
    • In 2020, businesses spent $129.5 billion on cloud infrastructure services and data centers
    • Global colocation data center market revenue could increase to more than $58 billion by 2025

… and more detailed data could be found in this article. Through big data analytics, modern businesses can forecast market fluctuations, discover more lucrative business opportunities, improve their efficiencies, beat their competitors, and provide a more customer-centric service and experience. Good read!

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