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    15Nov, 2023
    Bitcoin miners make money ahead of ‘halving’

    Bitcoin miners are making hay while the sun shines.

    The business has been yanked out of the doldrums by the cryptocurrency’s recent rally—and now mining companies are racing to lock in profits before bitcoin’s “halving” when rewards for producing the tokens are cut in half.

    The next halving is expected in April 2024, a process designed to slow the release of bitcoin, whose supply is capped at 21 million—of which 19 million have already been mined.

    “You’re seeing a lot of urgency to plug rigs in ahead of the halving,” said Gregory Lewis, analyst at brokerage BTIG that covers the 13 biggest US-listed bitcoin miners.

    Bitcoin’s hashrate—a measure of the computational power needed to mine a coin—has spiked to an all-time high, according to crypto platform Blockchain.com. That means miners are having to use more and more power and speed to crack the complex maths puzzles that earn them a bitcoin.

    Analysts at J.P. Morgan estimate the hashrate has hit record highs for 11 consecutive months, including a historic surge in October.

    Playing the game

    Bitcoin has risen about 37% in the past month to around $37,000 after months of listlessness, a rebound that’s encouraged miners to hook up their powerful computers to crack the puzzles and sell newly minted coins.

    The 30-day average of revenue earned by miners has improved steadily this year to hit an 18-month at $32.46 million on November 11, blockchain.com data shows.

    However, mining—a highly energy-intensive process—is still not as profitable as in its 2021 heyday.

    A measure of miners’ earnings from using 1 petahash per second of computing power in a day has risen to over $81 from $70 at the start of November but remains well below a peak of $127 in early May, according to mining data platform Hashrate Index.

    With six months to go till miners’ share of rewards is slashed, they are looking for ways to keep their margins from shrinking in the highly competitive environment.

    “Every halving forces miners not playing that game at a high enough level to get washed out,” said William Szamosszegi, CEO of mining company Sazmining.

    Halving opportunity

    Bitcoin prices have typically rallied in the past following halvings. Six months after the first halving in 2012, the price jumped to $126 from $12. After the second halving in 2016, it went to $1,000 from $654 within seven months and in 2020 it shot up to $18,040 from $8,570 in the same time period.

    Bitcoin’s third halving in 2020 brought down miner rewards to 6.25 bitcoin per block and the upcoming one is set to push it down to 3.125 in April.

    At current prices, mining each block reaps $231,250.

    Matteo Greco, analyst at digital asset investment company Fineqia International, said many mining companies were upgrading their equipment and boosting their hashrate power to stay competitive.

    To conserve their profit margins, some players have resorted to moving their operations to Central American countries where energy prices are more affordable, and governments friendlier to cryptocurrencies.

    “It’s too early to say if all bitcoin miners are out of the wood,” said Ludovic Thomas, portfolio manager at Swiss-based Criptonite Asset Management that invests in digital assets. “Profitability increase always leads to network hashrate and difficulty increase.”

    Resource : https://www.cnbctv18.com/cryptocurrency/bitcoin-miners-make-money-ahead-of-halving-18322721.htm

    14Nov, 2023
    Twisted magnets make brain-inspired computing more adaptable

    A form of brain-inspired computing that exploits the intrinsic physical properties of a material to dramatically reduce energy use is now a step closer to reality, thanks to a new study led by UCL and Imperial College London researchers.

    In the new study, published in the journal Nature Materials, an international team of researchers used chiral (twisted) magnets as their computational medium and found that, by applying an external magnetic field and changing temperature, the physical properties of these materials could be adapted to suit different machine-learning tasks.

    Such an approach, known as physical reservoir computing, has until now been limited due to its lack of reconfigurability. This is because a material’s physical properties may allow it to excel at a certain subset of computing tasks but not others.

    In the new study, published in the journal Nature Materials, an international team of researchers used chiral (twisted) magnets as their computational medium and found that, by applying an external magnetic field and changing temperature, the physical properties of these materials could be adapted to suit different machine-learning tasks.

    Dr Oscar Lee (London Centre for Nanotechnology at UCL and UCL Department of Electronic & Electrical Engineering), the lead author of the paper, said: “This work brings us a step closer to realising the full potential of physical reservoirs to create computers that not only require significantly less energy, but also adapt their computational properties to perform optimally across various tasks, just like our brains.

    “The next step is to identify materials and device architectures that are commercially viable and scalable.”

    Traditional computing consumes large amounts of electricity. This is partly because it has separate units for data storage and processing, meaning information has to be shuffled constantly between the two, wasting energy and producing heat. This is particularly a problem for machine learning, which requires vast datasets for processing. Training one large AI model can generate hundreds of tonnes of carbon dioxide.

    Physical reservoir computing is one of several neuromorphic (or brain inspired) approaches that aims to remove the need for distinct memory and processing units, facilitating more efficient ways to process data. In addition to being a more sustainable alternative to conventional computing, physical reservoir computing could be integrated into existing circuitry to provide additional capabilities that are also energy efficient.

    In the study, involving researchers in Japan and Germany, the team used a vector network analyser to determine the energy absorption of chiral magnets at different magnetic field strengths and temperatures ranging from -269 °C to room temperature.

    They found that different magnetic phases of chiral magnets excelled at different types of computing task. The skyrmion phase, where magnetised particles are swirling in a vortex-like pattern, had a potent memory capacity apt for forecasting tasks. The conical phase, meanwhile, had little memory, but its non-linearity was ideal for transformation tasks and classification — for instance, identifying if an animal is a cat or dog.

    Co-author Dr Jack Gartside, of Imperial College London, said: “Our collaborators at UCL in the group of Professor Hidekazu Kurebayashi recently identified a promising set of materials for powering unconventional computing. These materials are special as they can support an especially rich and varied range of magnetic textures. Working with the lead author Dr Oscar Lee, the Imperial College London group [led by Dr Gartside, Kilian Stenning and Professor Will Branford] designed a neuromorphic computing architecture to leverage the complex material properties to match the demands of a diverse set of challenging tasks. This gave great results, and showed how reconfiguring physical phases can directly tailor neuromorphic computing performance.”

    The work also involved researchers at the University of Tokyo and Technische Universität München and was supported by the Leverhulme Trust, Engineering and Physical Sciences Research Council (EPSRC), Imperial College London President’s Excellence Fund for Frontier Research, Royal Academy of Engineering, the Japan Science and Technology Agency, Katsu Research Encouragement Award, Asahi Glass Foundation, and the DFG (German Research Foundation).

    Resource : https://www.sciencedaily.com/releases/2023/11/231113111626.htm

    14Nov, 2023
    Nvidia upgrades flagship chip to handle bigger AI systems

    vidia added new features to its top-of-the-line chip for artificial intelligence, saying the new offering will start to roll out next year with Amazon, Google and Oracle

    Nvidia on Monday added new features to its top-of-the-line chip for artificial intelligence, saying the new offering will start to roll out next year with Amazon.com, Alphabet’s Google and Oracle.

    The H200, as the chip is called, will overtake Nvidia’s current top H100 chip. The primary upgrade is more high-bandwidth memory, one of the costliest parts of the chip that defines how much data it can process quickly.

    Nvidia dominates the market for AI chips and powers OpenAI’s ChatGPT service and many similar generative AI services that respond to queries with human-like writing. The addition of more high-bandwidth memory and a faster connection to the chip’s processing elements means that such services will be able to spit out an answer more quickly.

    The H200 has 141 gigabytes of high-bandwidth memory, up from 80 gigabytes in its previous H100. Nvidia did not disclose its suppliers for the memory on the new chip, but Micron Technology said in September that it was working to become an Nvidia supplier.

    Nvidia also buys memory from Korea’s SK Hynix, which said last month that AI chips are helping to revive sales.

    Nvidia on Wednesday said that Amazon Web Services, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure will be among the first cloud service providers to offer access to H200 chips, in addition to specialty AI cloud providers CoreWeave, Lambda and Vultr.

    Resource : https://www.thehindu.com/sci-tech/technology/nvidia-upgrades-flagship-chip-to-handle-bigger-ai-systems/article67531019.ece

    10Nov, 2023
    New BlazeStealer Malware in PyPI Targets Developers

    A new set of malicious Python packages has been discovered on the Python Package Index (PyPI) repository. These packages masquerade as harmless obfuscation tools but contain a malware called BlazeStealer, reported Checkmarx.

    Diving into details

    • The campaign started in January 2023 and includes eight packages – Pyobftoexe, Pyobfusfile, Pyobfexecute, Pyobfpremium, Pyobflite, Pyobfadvance, Pyobfuse, and pyobfgood. 
    • The BlazeStealer malware can execute a number of malicious actions on the infected host, including harvesting sensitive information such as passwords and screenshots, executing arbitrary commands, encrypting files, and disabling Microsoft Defender Antivirus.
    • The malware runs a Discord bot to facilitate communication between the threat actor and the infected system.
    • Most downloads originated from the U.S., China, and Russia, followed by Ireland, Hong Kong, Croatia, France, and Spain.

    Related incidents

    • Phylum uncovered a set of npm modules—puma-com, erc20-testenv, blockledger, cryptotransact, and chainflow–that can stealthily deliver a next-stage malware.
    • In October, Checkmarx observed a sophisticated attacker deploying malicious packages in PyPi and npm, accumulating nearly 75,000 downloads. The campaign was launched in April.

    The bottom line

    Open-source software provides a rich environment for germinating new ideas, but it also requires a healthy dose of skepticism. Developers must stay alert and thoroughly assess the reliability and safety of packages before incorporating them into their work.

    Resource : https://cyware.com/news/new-blazestealer-malware-in-pypi-targets-developers-666fe1bd

    10Nov, 2023
    GitHub Enhances Security Capabilities With AI

    Microsoft-owned code hosting platform GitHub today announced the public preview of three AI-powered features in GitHub Advanced Security.

    Available for GitHub Enterprise Cloud and Enterprise Server customers, Advanced Security provides a series of features to help maintain and improve the quality of code. Some of these features, such as Dependabot, are also available for public repositories.

    In a push for proactive security, GitHub has released tens of new capabilities to Advanced Security over the past year, and is now adding AI into the mix, “to revolutionize how developers build secure applications from the get-go”.

    In addition to code scanning, the platform now offers an ‘autofix’ capability, where AI-generated fixes will be delivered for CodeQL, JavaScript, and TypeScript alerts in developers’ pull requests, enabling them to address issues immediately.

    “These are not just any fixes, but precise, actionable suggestions that will allow you to quickly understand what the vulnerability is and how to remediate it. You can instantly commit these fixes to your code, helping you resolve issues faster and preventing new vulnerabilities from creeping into your codebases,” GitHub says.

    The platform is also leveraging the latest LLMs to identify leaked passwords with lower false positives. The capability is offered as part of secret scanning, currently in limited public beta.

    GitHub’s secret scanning program has 180 partners and provides more than 225 patterns for scanning, and is now leveraging AI to make it easier for code maintainers to create custom patterns to detect secrets unique to their organizations.

    “Through this form-based experience, all you have to do is answer a few simple questions to auto-generate custom patterns in the form of regular expressions. This new feature enables you to execute dry runs in real time to ensure proper scanning before saving the newly created pattern,” GitHub explains.

    Additionally, the platform has updated the security overview dashboard to provide security managers and administrators with access to an analysis of their security alerts and a better view of their security posture, based on risks, remediation, and prevention.

    “We’re thrilled to harness the power of AI to improve the relevance of alerts, speed up remediation, and improve the administrative experience—with the ultimate goal of making your teams happier and more productive, and your code more secure,” GitHub says.

    A spike in generative AI repositories

    Also today, GitHub released a new iteration of its Octoverse report, revealing that an increasing number of developers are building open source generative AI projects, which have made it to “the top 10 most popular open source projects by contributor count in 2023”.

    The number of generative AI projects on GitHub in the first half of 2023 more than doubled compared to the entire 2022, and developers have progressed from research to using pre-trained models and APIs to create generative AI-powered applications.

    Building on top of foundation models, such as ChatGPT, developers leverage LLMs to create APIs, assistants, bots, mobile applications, and plugins, laying the groundwork for mainstream adoption.

    “With almost all developers (92%) using or experimenting with AI coding tools, we expect open source developers to drive the next wave of AI innovation on GitHub,” the platform says.

    The top 20 open source generative AI projects on GitHub are owned by individuals, but the platform expects organizations to start using pre-trained AI models too, as more developers become accustomed to them.

    In terms of contributions to generative AI projects, GitHub has observed a 148% year-over-year growth, with the US, India, and Japan leading the trend, and Hong Kong, the UK, and Brazil following.

    “As more and more developers gain familiarity with building generative AI-powered applications, we expect a growing talent pool to bolster businesses that seek to develop their own AI-powered products and services,” GitHub notes.

    Today, the platform also announced the adoption of LLMs for GitHub Copilot, the AI developer tool that has more than one million paid users. In December, the tool’s users will have access to Copilot Chat, which leverages LLMs to help developers identify errors, debug code, and more.

    “Copilot Chat will be generally available in December 2023 as part of your existing GitHub Copilot subscription, for organizations and individuals. This offering is also available at no cost to verified teachers, students, and maintainers of popular open source projects,” GitHub announced today.

    Resource : https://www.securityweek.com/github-enhances-security-capabilities-with-ai/?web_view=true

    8Nov, 2023
    Performance Development: Unlock Your Team’s Potential

    SHRM defines performance management as “the process of maintaining or improving employee job performance through the use of performance assessment tools, coaching, and counseling as well as providing continuous feedback.”

    But far too many organizations stop at the first part — performance assessment — and miss the opportunity to actually improve employee performance. Only about one in four employees strongly agree that their manager provides meaningful feedback to them or that the feedback they receive helps them do better work. And only 21% of employees strongly agree that their performance is managed in a way that motivates them to do outstanding work.

    Best-in-class organizations are integrating continuous feedback and development to enable more effective performance management. This approach is often referred to as performance development — think of it as the place where performance management meets career development — and it can be a great way to unlock your team members’ full potential.

    The benefits of performance development

    Performance development goes beyond traditional employee reviews to focus on fostering continuous growth, skills enhancement, and career progression.

    Investing in a more robust approach to performance management has many benefits, including: 

    • Building emerging skill sets. Skills sets for jobs have changed by around 25% since 2015 — and this number is expected to grow to 65% by 2030. Effective performance management can help your team members identify and learn the in-demand and emerging skills they need to be successful in their current roles — and in their future ones. 
    • Increasing employee engagement. Performance development demonstrates the direct connection between feedback and career growth, motivating employees to go above and beyond at work. In fact, Gallup found that development is a top driver of employee engagement.
    • Reducing turnover. Continuous feedback and development shows your organization’s commitment to an employee’s long-term success, making your team members more likely to stay. The Josh Bersin Company found that organizations that offer ongoing skill development to their employees are 7.2x more likely to retain and engage their employees than those that don’t.
    • Improving business outcomes. Upskilling, engaging, and retaining talented team members through effective performance development practices can make a tremendous impact on your organization’s success. Companies that facilitate career development are 4x more likely to innovate effectively and 2.6x more likely to exceed financial targets.

    Building a performance management program that encourages career development

    Effective performance management is more than an annual event — it’s an ongoing process of goal setting, employee development, performance evaluation, and rewards. Each should be discussed regularly to nurture an engaged, motivated, and highly skilled workforce.

    Align on goals and performance expectations

    Just 50% of employees clearly understand what’s expected of them at work and only 21% strongly agree they have performance metrics that are within their control. Ambiguity and uncertainty around job expectations can hinder performance and negatively impact engagement.

    Discussing goals and expectations with each of your team members is a critical step toward effective performance management. Employees should understand how their success is being measured and feel empowered to accomplish their goals.

    Begin discussions on goal setting during your employee onboarding process by reviewing the job description, organizational goals, and your team member’s expected impact. Work together to build achievable short- and long-term goals, revisiting them during check-ins and performance reviews to gauge progress and make adjustments. 

    Employees whose managers involve them in goal setting are 3.6x more likely than other employees to be engaged, making this a worthwhile step in your performance management process.

    Build and maintain employee development plans

    Every employee has opportunities to learn and develop — and most want to. More than four out of five employees (83%) say that improving their skills is one of their top priorities. 

    Hold regular conversations with your team members to learn about each person’s professional growth goals, career aspirations, and skills they’d like to master. Then find the intersection of your team member’s development goals and your business needs to create a personalized performance development plan for each employee. 

    Performance development should go beyond addressing areas for improvement to also include honing strengths, learning emerging skills, and reskilling. Employees’ top motivation to learn is progress toward career goals, so it’s crucial to get your team members’ feedback and buy-in around their development plan to ensure alignment.

    Update development plans as your team members acquire new skills and identify additional opportunities for professional growth. The most effective development plans are flexible to accommodate evolving needs and interests.

    Provide continuous feedback

    Only 21% of U.S. employees strongly agree they have received meaningful feedback in the last week, with nearly half saying they receive feedback a few times a year or less. In other words, most employees don’t get enough performance feedback to understand what they’re doing well or when they need a course correction.

    Effective performance development requires that feedback be given consistently so employees have the guidance they need to be successful in their roles. Things you can do to make sure this happens include:

    • Initiate casual conversations. Let employees know when you see commendable efforts or teachable moments in their day-to-day work. Frequent feedback lets your team members know how you feel about their current performance and guides their development. Record the feedback in your performance management system so it can be referenced during future performance discussions.
    • Plan regular check-ins. Schedule regular one-on-one meetings to discuss progress toward goals, challenges, and development needs. These informal check-ins are a great opportunity to go in-depth on performance development discussions so you can make necessary adjustments to employee goals and development plans. 
    • Conduct regular performance evaluations. Plan comprehensive performance reviews at regular intervals to assess your employee’s overall performance and goal attainment. If you do performance development well, employees shouldn’t be hearing any feedback for the first time during the review process.

    Reward your team members for professional development

    Rewarding your team members for professional development acknowledges their effort and demonstrates the value your organization places on learning and growth. It can also help you retain employees: Compensation and career progression are among the top reasons for turnover.

    Offer raises and promotions as appropriate to reward your team members for developing their skill sets and gaining new experiences. This is particularly important if your employee’s new competencies or responsibilities qualify them for a higher pay grade or job level according to your compensation strategy.

    Final thoughts: Effective performance management is an ongoing process

    Gone are the days where an annual review is considered sufficient to manage employee performance. Modern teams encourage ongoing performance development to help employees achieve professional growth and meet evolving organizational goals. This approach can help you unlock your team’s full potential and drive your company’s success.

    Resource : https://www.linkedin.com/business/talent/blog/learning-and-development/performance-development

    8Nov, 2023
    The 10 most in-demand hard skills for 2023

    Technical roles are some of the most competitive for employers to fill, so it’s not surprising that many of the most in-demand hard skills align with these roles.

    The most in-demand hard skills this year are:

    1. Software development

    The COVID-19 pandemic accelerated the digital transformation and software development skills are needed to support this shift. Several popular programming languages, including Python, Java, and JavaScript, are also among the most in-demand hard skills for 2023.

    Reskill/upskill: Programming Foundations: Fundamentals with Annyce Davis. Get certified via this learning path: Career Essentials in Software Development

    2. SQL

    Many companies manage and analyze large, complex data sets in order to perform key business functions. SQL is an essential skill to retrieve and understand that data so it can be used to make informed business decisions.

    Reskill/upskill: SQL Essential Training with Walter Shields

    3. Finance

    Finance skills have always been a core need for most businesses, though looming economic uncertainty makes it more important for companies to get their finances in order. Careful planning can help companies forecast for various scenarios so they can adapt to unpredictable market conditions — whether that means an economic contraction or expansion.

    Reskill/upskill: Reading Corporate Financial Statements with Denise Probert

    4. Python

    Python is one of the most used programming languages today — and it will likely remain so for the foreseeable future. Python’s compatibility with all major operating systems and wide range of use cases makes it a worthwhile skill for technical workers to master.

    Reskill/upskill: Python Essential Training with Ryan Mitchell

    5. Java

    Java is another popular open-source programming language. Like Python, it’s platform-independent and has a broad range of applications. It’s most useful for designing web and phone apps, as well as cloud computing, making it hyper-relevant in our increasingly digital world.

    Reskill/upskill: Hands-On Introduction: Java with Angie Jones

    6. Data analysis

    Data is collected in every business function and must be analyzed to gain insights that can be used to make informed decisions. Effective data analytics can help organizations optimize performance and reduce costs.

    Reskill/upskill: Learning Data Analytics: 1 Foundations with Robin Hunt. Get certified with this learning path: Career Essentials in Data Analysis

    7. JavaScript

    JavaScript is a scripting language that’s used to develop dynamic web pages and platforms that automatically update with the latest information and multimedia required. As the most commonly used programming language, JavaScript is already familiar to many developers.

    Reskill/upskill: JavaScript Essential Training with Morten Rand-Hendriksen

    8. Cloud computing

    Cloud computing has largely displaced on-premise software due to increased accessibility, scalability, and cost savings. Engineers with cloud computing skills are still in very high demand as companies build and maintain these solutions. 

    9. Operations

    Operations skills help organizations manage their resources and processes so they run more efficiently. This can result in improved productivity, lower costs, and a stronger competitive advantage.

    Reskill/upskill: Quality Management for Operational Excellence with Richard Chua

    10. Customer relationship management (CRM)

    It’s easier — and less expensive — to retain an existing customer than it is to find a new one. Customer relationship management skills enable workers to build strong relationships with their current and prospective customers so they can increase loyalty and repeat business.

    Resource : https://www.linkedin.com/business/talent/blog/talent-strategy/linkedin-most-in-demand-hard-and-soft-skills

    7Nov, 2023
    NASA Finds Record-Breaking Black Hole Using ‘Cosmic Magnifying Glass’

    Astronomers using two NASA space telescopes have found one of the farthest black holes from the solar system using a rare alignment of galaxies to act as a magnifying glass.

    Existing just 470 million years after the Big Bang—the event that’s thought to have created our universe 13.8 billion years ago—it’s the most distant black hole yet seen in X-rays. Neither wavelength of light is visible to humans.

    It was found using both the James Webb Space Telescope, which sees the universe in infrared, and the Chandra X-ray Observatory, which sees in x-rays.

    Remarkably Distant

    “We needed Webb to find this remarkably distant galaxy and Chandra to find its supermassive black hole,” said Akos Bogdan of the Center for Astrophysics, Harvard & Smithsonian (CfA), lead author of a paper published today in the journal Nature Astronomy. “We also took advantage of a cosmic magnifying glass that boosted the amount of light we detected.”

    The black hole—which is at an earlier stage of development that any found before—was found in a galaxy called UHZ1. It’s in a cluster of galaxies called Abell 2744, which exists about 3.5 billion light-years from the solar system. Nicknamed Pandora’s Cluster, Abell 2744 is a megacluster of three separate clusters of galaxies and a stunning 50,000 objects.

    However, JWST observations revealed UHZ1 to be behind the cluster, a whopping 13.2 billion light-years from the solar system. That makes it just 3% of the universe’s current age.

    Einstein Ring

    JWST was able to make the discovery thanks to gravitational lensing. It describes a scenario when the gravitational field of a foreground object is so intense that it distorts the space around it and bends the light from an object behind it into circular rings, both revealing its existence and magnifying it. It’s also known as an “Einstein Ring” because it was predicted by the famous physicist Albert Einstein.

    Gravitational lensing is the best way to infer the presence of incredibly distant objects and measure their mass. In this case the black hole’s mass is similar to that of its host galaxy—between 10 and 100 million times the mass of our sun. That’s way more mass than expected.

    Sure Signs

    Once JWST had located it, Chandra spent a couple of weeks observing X-ray light coming from the galaxy, a sure sign of a growing supermassive black hole. Acting as a gravitational lens, Abell 2744 magnified the background galaxy by a factor of four.

    The observations could help scientists figure out how black holes at the beginning of the universe appear to have grown so quickly. The paper suggests that this particularly black hole was born big.

    “There are physical limits on how quickly black holes can grow once they’ve formed, but ones that are born more massive have a head start,” said co-author Andy Goulding of Princeton University. “It’s like planting a sapling, which takes less time to grow into a full-size tree than if you started with only a seed.”

    Resource : https://www.forbes.com/sites/jamiecartereurope/2023/11/06/nasa-finds-record-breaking-black-hole-using-cosmic-magnifying-glass/?sh=2a9aefdf2324

    7Nov, 2023
    Google Launches Generative AI Training Resources on Google Cloud

    This initiative aims to empower individuals and organisations by equipping them with the necessary knowledge and skills to leverage the potential of Generative AI across various domains.

    Within the Google Cloud Skills Boost platform, two comprehensive learning paths have been unveiled:

    Introduction to Generative AI: This pathway caters to individuals in non-technical roles, encompassing areas such as sales, marketing, human resources, and operations.

    It offers introductory, non-technical courses tailored to provide a foundational understanding of Generative AI, its ethical considerations, and its influence on business processes.

    Generative AI for Developers: Targeted at software developers, machine learning engineers, and data scientists, this path provides technical, hands-on labs, and courses that delve deep into practical aspects of working with Generative AI. It also explores the use of Google Cloud services such as Generative AI Studio and Vertex AI.

    Both learning paths feature a blend of theoretical knowledge and practical experience, comprising video courses, hands-on labs, and opportunities to earn skill badges, which serve as valuable credentials for career advancement.

    Google has underscored its commitment to keeping these training materials up to date, ensuring their alignment with the latest developments in the rapidly evolving field of Generative AI.

    Introductory Path:

    • Google’s “Introduction to Generative AI” course is offered at no cost and can be completed in a mere 45 minutes.
    • This non-technical pathway covers the fundamental principles of responsible AI and elucidates how Generative AI can impact diverse facets of business operations.
    • Completing this path earns participants the coveted Generative AI Fundamentals skill badge, signifying their foundational knowledge of Google Cloud’s Generative AI technology.
    • The full introductory path, which includes additional courses like ‘Introduction to Giant Language Models’ and ‘Introduction to Responsible AI,’ typically takes approximately two hours to complete.

    Advanced Path:

    • Tailored for app developers, machine learning engineers, and data scientists, the “Generative AI for Developers” course demands learners to first complete prerequisite courses, namely “Introduction to Responsible AI” and “Generative AI Fundamentals.”
    • Notably, the advanced path is not offered for free; it requires the use of Google Cloud credits to access more advanced technical labs, including those related to Generative AI Studio and Vertex AI.
    • Subscribers to the Google Cloud Innovators Plus plan gain access to all Generative AI content and enjoy a full year of on-demand training through the Google Cloud Skills Boost program.

    Hands-On Experience With Labs:

    Google Cloud facilitates hands-on learning through a range of Generative AI labs, allowing learners to gain practical experience by directly engaging with the platform.

    Available labs, along with the corresponding number of Google Cloud credits required for participation, encompass:

    • Get Started with Generative AI Studio (one credit)
    • Generative AI with Vertex AI: Getting Started (one credit)
    • Generative AI with Vertex AI: Prompt Design (one credit)
    • Vertex AI PaLM API: Quick Start (one credit)
    • Integrate Search in Applications Using Gen AI App Builder (5 credits)
    • Prompt Design using PaLM (one credit)
    • Explore and Evaluate Models using Model Garden (5 credits)

    Collaboration With DeepLearning.AI:

    • In a collaborative effort with DeepLearning.AI, spearheaded by renowned AI expert Andrew Ng, Google Cloud offers an additional course titled “Understanding and Applying Text Embeddings with Vertex AI.”
    • This course is provided free of charge and offers valuable insights into various advanced AI applications, including classification, outlier detection, text clustering, and semantic search.

    Google’s commitment to democratising AI education and fostering innovation in Generative AI is evident through these comprehensive training resources, now accessible to a global audience through the Google Cloud Skills Boost platform.

    For more details on Google’s Generative AI training resources and access information, please visit the Google Cloud Skills Boost website.

    No-Cost Introduction to Generative AI Course

    The Introduction to Generative AI course is ideal for individuals who want to grasp the fundamentals of this transformative technology but have limited time to spare.

    In just 45 minutes, participants can gain a foundational understanding of Generative AI, its potential applications, and its ethical considerations.

    For those who find themselves hungry for more knowledge after completing the introductory course, Google offers the opportunity to continue their learning journey at no cost.

    By pursuing the extended learning path, learners can earn the prestigious Generative AI digital skill badge

    The skill badge encompasses not only the introductory course but also two additional courses:

    • Introduction to Large Language Models: This course delves into the intricacies of large language models, providing learners with insights into their capabilities and applications.
    • Introduction to Responsible AI: This course explores the ethical dimensions of AI and emphasizes responsible AI practices.

    In total, completing the Generative AI Fundamentals skill badge takes approximately two hours. Participants who successfully complete this extended learning path will be awarded a digital skill badge.

    The badge serves as a valuable credential that can be proudly displayed on resumes and shared across social media channels, certifying the individual’s foundational understanding of Google Cloud’s Generative AI technology.

    Innovators Plus Subscription

    A notable addition to Google’s offerings is the Innovators Plus Subscription. The subscription provides access not only to Generative AI content but also unlocks the entire Google Cloud Skills Boost catalog of on-demand training resources for an entire year.

    Priced at just $299, subscribers gain access to developer benefits worth $1,500, which includes up to $1,000 in Google Cloud credits.

    Key features of the Innovators Plus Subscription include:

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    Resource : https://www.techbusinessnews.com.au/news/google-launches-generative-ai-training-resources-on-google-cloud/

    6Nov, 2023
    Role of AI in management education

    With the rapidly accelerating use of artificial intelligence and machine learning across segments, b-schools are in the process of updating their curricula in these areas. They are also integrating AI into their teaching methodology.

    Sangeeta Shah Bhardwaj, professor (information management) at MDI Gurgaon, says that though there may be business leaders who are apprehensive about AI, they would have no choice but to adopt it when others start using AI-powered tools. MDI, which has a programme in business analytics, has also introduced courses like geospatial AI and AI in marketing. The geospatial AI course looks at the impact location data is having on organisations and in the startup ecosystem. It will introduce to students the principles for assessing or creating location AI-based products and interfaces.

    “AI is being built as part of the process of learning management systems,” says Bhardwaj. “For instance, if there is an online group discussion, AI-enabled LMS will evaluate how students performed and will bring out traits like aggressiveness among other behaviour. This can help a professor in engaging students better.” She adds that students can also get personalised feedback regarding their career path with the help of AI.

    However, while AI can be a good supplement, especially in quantifiable business processes such as finance, operations, supply chain and sales, it may not solve the complexities our business leaders face. “A few months ago, an American lawyer used AI to prepare a case,” says Vivek Suneja, dean, FMS Delhi. “When the case went to court, it had a lot of incorrect information. AI manufactured information; basically it falsified data.”

    Moreover, there are limitations to the use of AI in human behavioural processes and decisions such as people engagement, succession planning, leadership and values and culture. Human behaviour is not easy to predict. AI will keep developing and become more sophisticated, but it may not be able to replace human traits, says Vishal Talwar, director, IMT Ghaziabad. “Nowadays, the students are more evolved in using such technologies and how management institutions are able to harness and ride that particular wave is something that we have to decide,” he says.

    Business leaders will also have to prioritise technology so that investments are made in the areas where the impact is on the quality of decision-making. “We have to look at robots and human beings working together,” says Ranjan Banerjee, dean, BITSoM, Mumbai. “Robots handle programmable aspects, leaving judgment, empathy, insight and relational aspects to humans. Management education will view technology not as a business function but as a horizontal, embedding technology in function.”