Hidden Apple Intelligence Features Revealed

Hidden Apple Intelligence Features Revealed

Apple’s latest iOS 18.1 beta 2 update brings a suite of advanced AI-driven features for Apple Intelligence designed to transform your user experience. These hidden gems leverage Apple’s innovative AI technology to automate tasks, enhance communication, and create personalized content, ultimately streamlining your daily interactions with your device. Let’s dive into the details of these innovative features.

Smart Reply: Effortless Email and Message Responses

The Smart Reply feature in iOS 18.1 takes the hassle out of responding to emails and messages. Intelligently analyzing the content of your incoming communications suggests complete, contextually relevant replies. Whether you receive an email requesting a meeting confirmation or a message asking for your availability, Smart Reply offers appropriate responses like “Yes, that works for me” or “Can we reschedule?” With just a tap, you can send a thoughtful reply, saving you valuable time and effort.

Microsoft Business Intelligence – Business Excellence
Microsoft Business Intelligence – Business Excellence

Call Recording and Transcription: Never Miss a Detail

iOS 18.1 introduces an innovative Call Recording feature in Apple Intelligence, that allows you to record phone calls directly on your iPhone. These recordings are conveniently saved in the Notes app, where you can also take synchronized notes during the call. But that’s not all – the feature also includes call transcription, allowing you to read through the entire conversation later. This proves invaluable for business calls, interviews, or any situation where you need to refer back to specific details mentioned during the call.

Reduce Interruptions Focus Mode: Stay Focused with Smart Notifications

The Reduce Interruptions Focus Mode of Apple Intelligence, harnesses the power of AI to intelligently manage your notifications, ensuring that only essential alerts break through when you need to concentrate. What sets this mode apart is its ability to highlight important notifications even when active. This means you can stay focused on your tasks without fear of missing critical updates. Whether it’s a reminder from your calendar or a message from an important contact, the AI ensures you receive the notifications that matter most.

Microsoft Power BI solution connect reports Business intelligence
Microsoft Power BI solution connect reports Business intelligence

Summaries: Bypass Paywalls and Ads for Streamlined Reading

The Summaries feature is a catalyst for avid readers and busy professionals alike. It provides concise text summarization for emails and web articles, allowing you to quickly grasp the key points without wading through lengthy content. But here’s the kicker – it can even bypass paywalls and ads in Safari, giving you a clean, ad-free reading experience. Whether you’re catching up on the latest news or skimming through a lengthy email thread, Summaries ensures you get the essential information without any distractions.

Create a Memory: Effortless Personalized Movies

With the Create a Memory feature, you can effortlessly generate stunning memory movies from your photos and videos. Simply describe the event or theme, and let the AI work its magic. It intelligently compiles relevant media from your library, creating a personalized movie that captures the essence of your memories. Whether it’s a vacation highlight reel, a family gathering montage, or a special occasion tribute, Create a Memory takes the hassle out of manual editing, allowing you to relive and share your precious moments with ease.

Microsoft readies new free version of its Power BI business
Microsoft readies new free version of its Power BI business

Type to Siri: Silent Interaction with Your Virtual Assistant

The Type to Siri feature introduces a new way to interact with your virtual assistant. Instead of relying solely on voice commands, you can now communicate with Siri through typed queries. This proves incredibly useful in situations where speaking is not possible or appropriate, such as in a quiet library or during a meeting. Simply type your request, whether it’s setting a reminder, sending a message, or searching for information, and Siri will silently assist you without disrupting your surroundings.

iOS 18.1’s hidden Apple Intelligence features mark a significant leap forward in mobile AI capabilities. By seamlessly integrating these advanced technologies into your daily interactions, Apple empowers you to:

Streamline communication with Smart Reply and Call Recording Stay focused with intelligent notification management in Reduce Interruptions Focus Mode Enjoy ad-free, summarized content with Summaries Create personalized memory movies effortlessly with Create a Memory Interact silently with Siri using Type to Siri

Power BI - Data Visualization Microsoft Power Platform
Power BI – Data Visualization Microsoft Power Platform

These features showcase Apple’s commitment to pushing the boundaries of what your iPhone can do, making everyday tasks more efficient, enjoyable, and tailored to your needs. With iOS 18.1 beta 2, you can experience the future of Apple Intelligence, where your device becomes an even more intelligent and intuitive companion in your daily life.

Source & Image Credit: iDB

Filed Under: Apple, Apple iPhone, Top News

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How artificial intelligence private equity performed in the power industry in Q2 2024

In value terms, artificial intelligence-related deal activity decreased in Q2 2024 compared with the previous quarter and as compared to Q2 2023. Related deal volume remained flat in Q2 2024 versus the previous quarter.

For further understanding of GlobalData’s Power Industry Mergers and Acquisitions Deals by Top Themes in Q2 2024 – Thematic Intelligence, buy the report here.

This content was updated on 26 July 2024

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Transforming Your Organization with the Power of Business Intelligence

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With the ability to drive strategic initiatives, make educated decisions and extract valuable insights from raw data, business intelligence (BI) has become a key enabler for organizational success. BI has revolutionized the way businesses operate and plan for the future in this age of intense competition and rapid technological advancement. One of the most powerful business intelligence tools available, Intellicus has provided tailored solutions to over 17,000 small and large businesses, enabling them to make data-driven decisions.

Understanding Business Intelligence

Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. It combines internal and external data sources into a logical framework that helps produce insights that can be put into action. Business intelligence is a valuable resource that facilitates managers, executives and stakeholders to make informed decisions.

Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. Essentially, BI transforms raw data into meaningful information that empowers organizations to make data-driven decisions.

The Four Pillars of Business Intelligence

Data Collection and Integration: Business Intelligence starts with the compilation of information from various sources, such as social media interactions, market trends, consumer profiles and sales statistics. This data must be integrated into a single platform in order to provide a comprehensive view and analysis.

Data Visualization and Analysis: BI tools analyze trends, patterns, and connections using sophisticated analytics. Visualization tools like dashboards, charts, and graphs transform complex data into understandable insights for efficient decision-making.

Predictive Analytics: BI doesn’t merely focus on the present; it anticipates the future. To predict future trends, predictive analytics uses machine learning models and statistical algorithms. This makes it possible for companies to plan ahead and adapt proactively.

Actionable Insights: BI aims to generate actionable insights, not just reports. These insights help optimize operations, identify new opportunities, and enhance overall performance.

The Transformative Impact of Business Intelligence Improved Decision Making

BI tools give businesses access to real-time data, which is essential for making timely, well-informed decisions. This eliminates the need for guesswork and intuition-based decisions in favor of data-driven ones. Additionally, BI tools, like dashboards and visualizations, present data in an understandable format, making it easier for decision-makers to quickly comprehend complex information and react to changes that may have an impact on the business.

Operational Efficiency

The operational efficiency of an organization can be greatly improved using business intelligence. By automating repetitive operations, BI solutions allow employees to concentrate on more important facets of the company. Furthermore, by highlighting areas in the business process that require improvement, BI tools enable firms to get rid of bottlenecks, simplify procedures and cut expenses. Customer satisfaction and service delivery are enhanced as a result.

Improved Bottom Line

Business Intelligence can assist companies in increasing revenue and sales by offering insightful information about consumer behavior. With the use of BI technologies, marketers can better focus their campaigns and boost sales by analyzing customer data to find trends, buying patterns and preferences. Additionally, organizations can use business intelligence to pinpoint successful consumer categories and concentrate their marketing efforts on them. Revenue growth and improved conversion rates are possible outcomes of this focused strategy.

Competitive Advantage

Business Intelligence provides a competitive edge in today’s data-driven world. Through the utilization of BI tools, companies can acquire comprehensive insights into the tactics, advantages and disadvantages of their rivals and utilize this data to formulate strategic plans. Similarly, it facilitates prompt market adaptation and can assist companies in recognizing customer behavior shifts and market trends.

Ethical Considerations in BI

The Future of Business Intelligence

Advancing technology promises a bright future for BI. AI and machine learning will enhance predictive analytics, enabling businesses to foresee trends and adapt quickly. Integrating BI with emerging technologies like IoT and blockchain will unlock new dimensions of data analysis and decision-making.

Conclusion

Business Intelligence has evolved from being a mere buzzword to a transformative force shaping the future of businesses. It empowers organizations to navigate complexities, capitalize on opportunities, and drive growth in an increasingly data-centric world. Embracing BI isn’t just an option; it’s a necessity for businesses aspiring to thrive in today’s competitive landscape.

repeating the info from intro [SD1]

This doesn’t fit right here… please change the placement [SD2]

Transforming Your Organization with the Power of Business Intelligence

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With the ability to drive strategic initiatives, make educated decisions and extract valuable insights from raw data, business intelligence (BI) has become a key enabler for organizational success. BI has revolutionized the way businesses operate and plan for the future in this age of intense competition and rapid technological advancement. One of the most powerful business intelligence tools available, Intellicus has provided tailored solutions to over 17,000 small and large businesses, enabling them to make data-driven decisions.

Understanding Business Intelligence

Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. It combines internal and external data sources into a logical framework that helps produce insights that can be put into action. Business intelligence is a valuable resource that facilitates managers, executives and stakeholders to make informed decisions.

Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. Essentially, BI transforms raw data into meaningful information that empowers organizations to make data-driven decisions.

The Four Pillars of Business Intelligence

Data Collection and Integration: Business Intelligence starts with the compilation of information from various sources, such as social media interactions, market trends, consumer profiles and sales statistics. This data must be integrated into a single platform in order to provide a comprehensive view and analysis.

Data Visualization and Analysis: BI tools analyze trends, patterns, and connections using sophisticated analytics. Visualization tools like dashboards, charts, and graphs transform complex data into understandable insights for efficient decision-making.

Predictive Analytics: BI doesn’t merely focus on the present; it anticipates the future. To predict future trends, predictive analytics uses machine learning models and statistical algorithms. This makes it possible for companies to plan ahead and adapt proactively.

Actionable Insights: BI aims to generate actionable insights, not just reports. These insights help optimize operations, identify new opportunities, and enhance overall performance.

The Transformative Impact of Business Intelligence Improved Decision Making

BI tools give businesses access to real-time data, which is essential for making timely, well-informed decisions. This eliminates the need for guesswork and intuition-based decisions in favor of data-driven ones. Additionally, BI tools, like dashboards and visualizations, present data in an understandable format, making it easier for decision-makers to quickly comprehend complex information and react to changes that may have an impact on the business.

Operational Efficiency

The operational efficiency of an organization can be greatly improved using business intelligence. By automating repetitive operations, BI solutions allow employees to concentrate on more important facets of the company. Furthermore, by highlighting areas in the business process that require improvement, BI tools enable firms to get rid of bottlenecks, simplify procedures and cut expenses. Customer satisfaction and service delivery are enhanced as a result.

Improved Bottom Line

Business Intelligence can assist companies in increasing revenue and sales by offering insightful information about consumer behavior. With the use of BI technologies, marketers can better focus their campaigns and boost sales by analyzing customer data to find trends, buying patterns and preferences. Additionally, organizations can use business intelligence to pinpoint successful consumer categories and concentrate their marketing efforts on them. Revenue growth and improved conversion rates are possible outcomes of this focused strategy.

Competitive Advantage

Business Intelligence provides a competitive edge in today’s data-driven world. Through the utilization of BI tools, companies can acquire comprehensive insights into the tactics, advantages and disadvantages of their rivals and utilize this data to formulate strategic plans. Similarly, it facilitates prompt market adaptation and can assist companies in recognizing customer behavior shifts and market trends.

Ethical Considerations in BI

The Future of Business Intelligence

Advancing technology promises a bright future for BI. AI and machine learning will enhance predictive analytics, enabling businesses to foresee trends and adapt quickly. Integrating BI with emerging technologies like IoT and blockchain will unlock new dimensions of data analysis and decision-making.

Conclusion

Business Intelligence has evolved from being a mere buzzword to a transformative force shaping the future of businesses. It empowers organizations to navigate complexities, capitalize on opportunities, and drive growth in an increasingly data-centric world. Embracing BI isn’t just an option; it’s a necessity for businesses aspiring to thrive in today’s competitive landscape.

repeating the info from intro [SD1]

This doesn’t fit right here… please change the placement [SD2]

AI’s Increasing Power Needs

The explosive growth of artificial intelligence (AI) has prompted the datacenter giants—including Google, Meta, Amazon, and Microsoft (whose datacenters run most AI software)—to start building super-sized hyperscale datacenters that require much more power—gigawatts instead of megawatts. These giant datacenters use existing semiconductor technology that challenges aging U.S. electrical grid infrastructure to meet their energy consumption needs, according to analysts.

For instance, Goldman Sachs estimates that just a single query to ChatGPT (generative pre-trained transformer chatbot) uses 10 times as much datacenter electrical energy than traditional AI functions like speech recognition, thus the rationale for more powerful hyperscale datacenters.

Today, traditional AI runs behind the scenes. For instance, natural language recognition (as when you speak to your computer) is an AI function that requires millions (for individual words) to billions (for complete sentences) of connections between virtual neurons and synapses in a “learning” neural network. Today these spoken-word learning functions are run in the background, during datacenter lulls. After learning to recognize every word in the dictionary, the neural network can be compressed into a much smaller, faster, runtime “inference engine” for real-time responses to users.

The new AI functions—called generative AI (GenAI)—use much larger learning neural networks with trillions of connections to accommodate not just the spoken words in the dictionary, like today’s speech recognition AIs, but which learn entire libraries of books (called large language models—LLMs) or vast sets of visual scenes (called vision transformers—ViTs). However, at runtime, transformers cannot be compressed into the same small, fast inference engines as happens in word recognition. The reason is that they don’t return simple words in response to your input, but instead compare your queries with trillions of examples in their gigantic neural networks and transform them—word by word—into responses that range in size from complete paragraphs to a whole white paper, or even to an entire book on the subject of your query.

By the end of the decade, even more computational power will be needed when GenAI applications progress to routinely returning entire works of art or, say, video documentaries from queries to ViTs, like “painting landscapes in the style of Vincent van Gogh,” according to Jim McGregor, founder and a principal analyst at Tirias Research.

“Once we get to mass adoption of visual-content creation with GenAI, the demand is going to be huge—we’ll need to increase datacenter performance/power exponentially,” said McGregor.

To support datacenters powerful enough to handle existing chat-caliber GenAI, Tirias’ latest report predicts U.S. datacenter energy consumption will increase from over 1.4 tera-Watt-hours (TWh) today to 67 TWh by 2028. Goldman Sachs estimates that when you add traditional AI to GenAI, about twice that amount of growth is expected in the same time period, resulting in AI consuming about 19% of overall datacenter energy power, or about 4% of total grid energy generation for all the U.S.

The way this strong growth in energy consumption from the grid will be met, according to Goldman Sachs report AI, Data Centers and the Coming US Power Demand Surge, is by transforming power generation for the grid from coal-fired electrical energy generation to “60% [natural] gas and 40% renewable sources [mainly solar and wind].” In addition, Bloomberg points out that the move to gas and renewable sources will include delaying the retirement of some coal-fired electricity generation plants nearest the newest hyperscale datacenters.

There is also a trend to prevent overloading of the grid with nuclear electrical energy generators dedicated to individual hyperscale datacenters, called small modular reactors (SMRs), said Rian Bahran, Assistant Director of the White House Office of Science and Technology Policy in his keynote at Data Center World 2024. Bahran said nuclear power should be added to the list of “clean” and “sustainable” energy sources to meet hyperscale datacenter energy consumption demands. In fact, Amazon has already purchased from Talen Energy, a nearly 1-gigaWatt-capable nuclear-powered datacenter campus in Salem, PA, powered by the adjacent 2.5-gigaWatt Susquehanna nuclear plant owned by Talen. Bahran also revealed that currently as many as two dozen SMRs are being constructed, each capable of generating bout 75 megawatts of electricity, on two datacenter campuses in Ohio and Pennsylvania.

At the same time, Microsoft is attempting to one-up fission reactors like SMRs by investing in nuclear-waste-free fusion reactors (partnering with Helion).

“No single silver bullet will solve this increasing need for more electrical energy sources, but it’s not as bad as some make it out to be, at least for the next generation beyond current technology datacenters,” said McGregor. “The way I see it, it’s like Moore’s Law [regarding the periodic doubling of transistor density]; we kept predicting its end, but every time we thought there was a roadblock, we found an innovation that got past it.”

Today’s hyperscale datacenters are using current semiconductor technologies and architectures, but innovation will stave off the unbridled increase in GenAI power consumption—in the long term—the same way innovation kept Moore’s Law moving forward, according to McGregor. That is, by finding new ways to increase performance while lowering power—with a new generation of hybrid stacks of CPUs, GPUs, and memory chips in the same package, with water-cooled server racks instead of air-cooled, with all-optical data connections—even chip-to-chip—instead of today’s mix of copper and fiber, and with larger water-cooled wafer-scale chips with trillions of transistors.

“The level of innovation in power reduction is phenomenal. This level of innovation rivals the start of the semiconductor industry and in many ways is even faster-growing. If technology stood still, then we would run out of available energy by the end of the decade,” according to McGregor. Yet according to Tirias’ GenAI predictions, the use of low-power hybrid CPU/GPU-based AI accelerators at datacenters will grow from 362,000 units today to 17.6 million in 2028.

“Take, for instance, Cerebras Systems AI chip that takes up an entire wafer with four trillion transistors,” said McGregor. The Cerebras next-generation water-cooled wafer-scale chip draws 50X less power for its four trillion transistors than today’s separate CPU-chip- and GPU-chip-based datacenter servers. The wafer-scale made-for-AI chip is currently being proven out in collaborations with researchers at Sandia National Laboratories, Lawrence Livermore National Lab, Los Alamos National Laboratory, and the National Nuclear Security Administration. It also will be integrated into future Dell servers for large-scale AI deployment.

Already available powering four of the top five positions on the 2024 Green 500 supercomputer list is the latest Nvidia hybrid CPU/GPU-based AI accelerator, which can replace multiple traditional servers for AI workloads, at a fraction of their current energy consumption. For instance, Nvidia user Pierre Spatz, head of quantitative research at Murex (Paris), reports in a blog that Nvidia’s latest AI accelerator, the Grace Hopper Superchip, is “not only the fastest processor [available today], but is also far more power-efficient—making green IT a reality.” According to Spatz, this Nvidia Grace Hopper Superchip boosts Murex’s financial-prediction software performance by 7X while simultaneously offering a 4X reduction in energy consumption.

Innovation Solving Crises

Nvidia is not the only hybrid CPU/GPU chip maker with faster AI execution at lower power. For instance, AMD won the 2022 top spot in the Green500 supercomputer ranking (and four of the top 10 slots in the Green500 2024 supercomputer ranking). AMD’s latest secret sauce for faster performance with lower energy consumption in its next-generation chips is hybrid stacking of multiple CPU, GPU, and I/O-to-optical fabric chips in the same package.

Cerebras has attached a water-cooled metal cold plate to the top of silicon chips to draw heat away more efficiently than by using cool air as in today’s datacenters.

Other chip makers also are accelerating their next-generation datacenter processors with power-saving hybrid multi-chip stacks. In addition, Intel, Samsung, and Taiwan Semiconductor Manufacturing Company (TSMC) are demonstrating 3D stacked transistors for their next-generation processors that substantially increase performance while saving power.

Semiconductor architects are also beginning to rethink the entire datacenter as a single system—like hybrid systems-on-a-chip—investing in sustainable, more energy-efficient architectures that, for instance, switch to water (instead of air) cooling for the racks in the entire datacenter. “The rear door heat exchanger, for instance, is based on water cooling that can reduce the energy consumption in the servers at high-density datacenters,” according to Laura DiDio, president and principal analyst of Information Technology Intelligence Consulting (ITIC).

Future datacenters also will make use of quick-switching strategies among multiple power sources, including solar, wind, natural gas, geothermal, grid, and nuclear reactors, said McGregor.

According to Jim Handy, general director of Objective Analysis, the popularity of AI has created an energy crisis, but not an unsolvable one.

“What is interesting to me in all these crises arguments, is that they happen over and over every time a new technology starts becoming widespread—the crisis predictors are just extrapolating from the current technologies, which doesn’t account for innovative solutions,” said Handy. “For instance, in the 1990s, the Internet began growing so fast that we had predictions that half the electrical energy of the world was going to be consumed by it. What happened? Innovation was able to keep up with demand. The same massive crisis argument happened again when bitcoin took off, but that too fizzled, and now we are hearing the same crisis arguments regarding the growth of AI.”

R. Colin Johnson is a Kyoto Prize Fellow who ​​has worked as a technology journalist ​for two decades.

Transforming Your Organization with the Power of Business Intelligence

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With the ability to drive strategic initiatives, make educated decisions and extract valuable insights from raw data, business intelligence (BI) has become a key enabler for organizational success. BI has revolutionized the way businesses operate and plan for the future in this age of intense competition and rapid technological advancement. One of the most powerful business intelligence tools available, Intellicus has provided tailored solutions to over 17,000 small and large businesses, enabling them to make data-driven decisions.

Understanding Business Intelligence

Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. It combines internal and external data sources into a logical framework that helps produce insights that can be put into action. Business intelligence is a valuable resource that facilitates managers, executives and stakeholders to make informed decisions.

Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. Essentially, BI transforms raw data into meaningful information that empowers organizations to make data-driven decisions.

The Four Pillars of Business Intelligence

Data Collection and Integration: Business Intelligence starts with the compilation of information from various sources, such as social media interactions, market trends, consumer profiles and sales statistics. This data must be integrated into a single platform in order to provide a comprehensive view and analysis.

Data Visualization and Analysis: BI tools analyze trends, patterns, and connections using sophisticated analytics. Visualization tools like dashboards, charts, and graphs transform complex data into understandable insights for efficient decision-making.

Predictive Analytics: BI doesn’t merely focus on the present; it anticipates the future. To predict future trends, predictive analytics uses machine learning models and statistical algorithms. This makes it possible for companies to plan ahead and adapt proactively.

Actionable Insights: BI aims to generate actionable insights, not just reports. These insights help optimize operations, identify new opportunities, and enhance overall performance.

The Transformative Impact of Business Intelligence Improved Decision Making

BI tools give businesses access to real-time data, which is essential for making timely, well-informed decisions. This eliminates the need for guesswork and intuition-based decisions in favor of data-driven ones. Additionally, BI tools, like dashboards and visualizations, present data in an understandable format, making it easier for decision-makers to quickly comprehend complex information and react to changes that may have an impact on the business.

Operational Efficiency

The operational efficiency of an organization can be greatly improved using business intelligence. By automating repetitive operations, BI solutions allow employees to concentrate on more important facets of the company. Furthermore, by highlighting areas in the business process that require improvement, BI tools enable firms to get rid of bottlenecks, simplify procedures and cut expenses. Customer satisfaction and service delivery are enhanced as a result.

Improved Bottom Line

Business Intelligence can assist companies in increasing revenue and sales by offering insightful information about consumer behavior. With the use of BI technologies, marketers can better focus their campaigns and boost sales by analyzing customer data to find trends, buying patterns and preferences. Additionally, organizations can use business intelligence to pinpoint successful consumer categories and concentrate their marketing efforts on them. Revenue growth and improved conversion rates are possible outcomes of this focused strategy.

Competitive Advantage

Business Intelligence provides a competitive edge in today’s data-driven world. Through the utilization of BI tools, companies can acquire comprehensive insights into the tactics, advantages and disadvantages of their rivals and utilize this data to formulate strategic plans. Similarly, it facilitates prompt market adaptation and can assist companies in recognizing customer behavior shifts and market trends.

Ethical Considerations in BI

The Future of Business Intelligence

Advancing technology promises a bright future for BI. AI and machine learning will enhance predictive analytics, enabling businesses to foresee trends and adapt quickly. Integrating BI with emerging technologies like IoT and blockchain will unlock new dimensions of data analysis and decision-making.

Conclusion

Business Intelligence has evolved from being a mere buzzword to a transformative force shaping the future of businesses. It empowers organizations to navigate complexities, capitalize on opportunities, and drive growth in an increasingly data-centric world. Embracing BI isn’t just an option; it’s a necessity for businesses aspiring to thrive in today’s competitive landscape.

repeating the info from intro [SD1]

This doesn’t fit right here… please change the placement [SD2]

AI’s Increasing Power Needs

The explosive growth of artificial intelligence (AI) has prompted the datacenter giants—including Google, Meta, Amazon, and Microsoft (whose datacenters run most AI software)—to start building super-sized hyperscale datacenters that require much more power—gigawatts instead of megawatts. These giant datacenters use existing semiconductor technology that challenges aging U.S. electrical grid infrastructure to meet their energy consumption needs, according to analysts.

For instance, Goldman Sachs estimates that just a single query to ChatGPT (generative pre-trained transformer chatbot) uses 10 times as much datacenter electrical energy than traditional AI functions like speech recognition, thus the rationale for more powerful hyperscale datacenters.

Today, traditional AI runs behind the scenes. For instance, natural language recognition (as when you speak to your computer) is an AI function that requires millions (for individual words) to billions (for complete sentences) of connections between virtual neurons and synapses in a “learning” neural network. Today these spoken-word learning functions are run in the background, during datacenter lulls. After learning to recognize every word in the dictionary, the neural network can be compressed into a much smaller, faster, runtime “inference engine” for real-time responses to users.

The new AI functions—called generative AI (GenAI)—use much larger learning neural networks with trillions of connections to accommodate not just the spoken words in the dictionary, like today’s speech recognition AIs, but which learn entire libraries of books (called large language models—LLMs) or vast sets of visual scenes (called vision transformers—ViTs). However, at runtime, transformers cannot be compressed into the same small, fast inference engines as happens in word recognition. The reason is that they don’t return simple words in response to your input, but instead compare your queries with trillions of examples in their gigantic neural networks and transform them—word by word—into responses that range in size from complete paragraphs to a whole white paper, or even to an entire book on the subject of your query.

By the end of the decade, even more computational power will be needed when GenAI applications progress to routinely returning entire works of art or, say, video documentaries from queries to ViTs, like “painting landscapes in the style of Vincent van Gogh,” according to Jim McGregor, founder and a principal analyst at Tirias Research.

“Once we get to mass adoption of visual-content creation with GenAI, the demand is going to be huge—we’ll need to increase datacenter performance/power exponentially,” said McGregor.

To support datacenters powerful enough to handle existing chat-caliber GenAI, Tirias’ latest report predicts U.S. datacenter energy consumption will increase from over 1.4 tera-Watt-hours (TWh) today to 67 TWh by 2028. Goldman Sachs estimates that when you add traditional AI to GenAI, about twice that amount of growth is expected in the same time period, resulting in AI consuming about 19% of overall datacenter energy power, or about 4% of total grid energy generation for all the U.S.

The way this strong growth in energy consumption from the grid will be met, according to Goldman Sachs report AI, Data Centers and the Coming US Power Demand Surge, is by transforming power generation for the grid from coal-fired electrical energy generation to “60% [natural] gas and 40% renewable sources [mainly solar and wind].” In addition, Bloomberg points out that the move to gas and renewable sources will include delaying the retirement of some coal-fired electricity generation plants nearest the newest hyperscale datacenters.

There is also a trend to prevent overloading of the grid with nuclear electrical energy generators dedicated to individual hyperscale datacenters, called small modular reactors (SMRs), said Rian Bahran, Assistant Director of the White House Office of Science and Technology Policy in his keynote at Data Center World 2024. Bahran said nuclear power should be added to the list of “clean” and “sustainable” energy sources to meet hyperscale datacenter energy consumption demands. In fact, Amazon has already purchased from Talen Energy, a nearly 1-gigaWatt-capable nuclear-powered datacenter campus in Salem, PA, powered by the adjacent 2.5-gigaWatt Susquehanna nuclear plant owned by Talen. Bahran also revealed that currently as many as two dozen SMRs are being constructed, each capable of generating bout 75 megawatts of electricity, on two datacenter campuses in Ohio and Pennsylvania.

At the same time, Microsoft is attempting to one-up fission reactors like SMRs by investing in nuclear-waste-free fusion reactors (partnering with Helion).

“No single silver bullet will solve this increasing need for more electrical energy sources, but it’s not as bad as some make it out to be, at least for the next generation beyond current technology datacenters,” said McGregor. “The way I see it, it’s like Moore’s Law [regarding the periodic doubling of transistor density]; we kept predicting its end, but every time we thought there was a roadblock, we found an innovation that got past it.”

Today’s hyperscale datacenters are using current semiconductor technologies and architectures, but innovation will stave off the unbridled increase in GenAI power consumption—in the long term—the same way innovation kept Moore’s Law moving forward, according to McGregor. That is, by finding new ways to increase performance while lowering power—with a new generation of hybrid stacks of CPUs, GPUs, and memory chips in the same package, with water-cooled server racks instead of air-cooled, with all-optical data connections—even chip-to-chip—instead of today’s mix of copper and fiber, and with larger water-cooled wafer-scale chips with trillions of transistors.

“The level of innovation in power reduction is phenomenal. This level of innovation rivals the start of the semiconductor industry and in many ways is even faster-growing. If technology stood still, then we would run out of available energy by the end of the decade,” according to McGregor. Yet according to Tirias’ GenAI predictions, the use of low-power hybrid CPU/GPU-based AI accelerators at datacenters will grow from 362,000 units today to 17.6 million in 2028.

“Take, for instance, Cerebras Systems AI chip that takes up an entire wafer with four trillion transistors,” said McGregor. The Cerebras next-generation water-cooled wafer-scale chip draws 50X less power for its four trillion transistors than today’s separate CPU-chip- and GPU-chip-based datacenter servers. The wafer-scale made-for-AI chip is currently being proven out in collaborations with researchers at Sandia National Laboratories, Lawrence Livermore National Lab, Los Alamos National Laboratory, and the National Nuclear Security Administration. It also will be integrated into future Dell servers for large-scale AI deployment.

Already available powering four of the top five positions on the 2024 Green 500 supercomputer list is the latest Nvidia hybrid CPU/GPU-based AI accelerator, which can replace multiple traditional servers for AI workloads, at a fraction of their current energy consumption. For instance, Nvidia user Pierre Spatz, head of quantitative research at Murex (Paris), reports in a blog that Nvidia’s latest AI accelerator, the Grace Hopper Superchip, is “not only the fastest processor [available today], but is also far more power-efficient—making green IT a reality.” According to Spatz, this Nvidia Grace Hopper Superchip boosts Murex’s financial-prediction software performance by 7X while simultaneously offering a 4X reduction in energy consumption.

Innovation Solving Crises

Nvidia is not the only hybrid CPU/GPU chip maker with faster AI execution at lower power. For instance, AMD won the 2022 top spot in the Green500 supercomputer ranking (and four of the top 10 slots in the Green500 2024 supercomputer ranking). AMD’s latest secret sauce for faster performance with lower energy consumption in its next-generation chips is hybrid stacking of multiple CPU, GPU, and I/O-to-optical fabric chips in the same package.

Cerebras has attached a water-cooled metal cold plate to the top of silicon chips to draw heat away more efficiently than by using cool air as in today’s datacenters.

Other chip makers also are accelerating their next-generation datacenter processors with power-saving hybrid multi-chip stacks. In addition, Intel, Samsung, and Taiwan Semiconductor Manufacturing Company (TSMC) are demonstrating 3D stacked transistors for their next-generation processors that substantially increase performance while saving power.

Semiconductor architects are also beginning to rethink the entire datacenter as a single system—like hybrid systems-on-a-chip—investing in sustainable, more energy-efficient architectures that, for instance, switch to water (instead of air) cooling for the racks in the entire datacenter. “The rear door heat exchanger, for instance, is based on water cooling that can reduce the energy consumption in the servers at high-density datacenters,” according to Laura DiDio, president and principal analyst of Information Technology Intelligence Consulting (ITIC).

Future datacenters also will make use of quick-switching strategies among multiple power sources, including solar, wind, natural gas, geothermal, grid, and nuclear reactors, said McGregor.

According to Jim Handy, general director of Objective Analysis, the popularity of AI has created an energy crisis, but not an unsolvable one.

“What is interesting to me in all these crises arguments, is that they happen over and over every time a new technology starts becoming widespread—the crisis predictors are just extrapolating from the current technologies, which doesn’t account for innovative solutions,” said Handy. “For instance, in the 1990s, the Internet began growing so fast that we had predictions that half the electrical energy of the world was going to be consumed by it. What happened? Innovation was able to keep up with demand. The same massive crisis argument happened again when bitcoin took off, but that too fizzled, and now we are hearing the same crisis arguments regarding the growth of AI.”

R. Colin Johnson is a Kyoto Prize Fellow who ​​has worked as a technology journalist ​for two decades.

Will artificial intelligence replace your financial advisor? Photo source: Wealth of Geeks

By Liam Gibson | Wealth of Geeks

A recent Deloitte report predicts 78% of retail investors will use generative AI applications as an investment advice source by 2027.

Don’t be surprised if conversations with your financial advisor soon feel relatively automated — you might be chatting with a bot.

The financial advisory industry is poised for dramatic Artificial Intelligence (AI) disruption. If this comes to pass, AI will become the leading source of retail investment advice, outstripping friends and family, social media, and even your local financial advisor.

Deloitte foresees retail investors leveraging broad-based generative AI applications tailored for investment advice to help make decisions. However, this is broader than that of AI-native companies. Many legacy financial institutions will also offer AI-powered financial advice engines as clients gain comfort with investment tools that utilize artificial intelligence.

Industry insiders have mixed opinions on the degree of AI disruption investors should expect to see in the near term.

Automatic Advice

An AI takeover of personal finance seems a far cry from the present. From the combustion engine to the internet, the lag between invention and society-wide adoption of new technologies is often longer than initial forecasts suggest.

Yet, unlike previous breakthroughs, consumer AI tools require no new hardware. With a few clicks and ubiquitous internet access, users can conduct quick web searches to locate AI resources. Generative AI applications are within reach of anyone with a Wi-Fi connection, making it the first time a massive technological revolution has been available so quickly.

The speed of AI adoption sets this technological advancement apart from those before it.

“Deloitte’s prediction for 2028 might seem bold, but the rapid advancements in AI technology and increasing consumer comfort with digital tools make this plausible,” says Jorey Bernstein, founder of Bernstein Investment Consultants. “There are already several AI financial planning apps like Betterment and Wealthfront that offer automated investment advice.”

Online investing tools and consumer wealth-tracking applications democratize financial planning by bringing down barriers blocking resources reserved for professional traders and advisors.

These advisor platforms are intuitive to use — no Zoom meeting required. After signing up, consumers set financial goals and complete a risk assessment. The AI-driven platforms utilize responses to create and manage diversified portfolios. They also handle tasks like portfolio rebalancing and tax-loss harvesting, offering a hands-off investment experience with minimal fees and personalized advice.

With readily available tools like these, paying a financial advisor to allocate a portfolio makes less sense.

“Investment management is becoming a commodity,” says Angela Dorsey, Founder and Financial Planner of Dorsey Wealth Management. “Advisors who only provide investment management are vulnerable to being replaced by AI.”

The Human Touch

Fortunately, many financial advisors likely have little to worry about when it comes to AI, as most offer services beyond investment management. Humans can delicately manage sensitive issues like estate and tax planning, offer broad life planning advice, and empower clients to achieve goals while assisting them during divorces or retirement.

Advisors believe this human touch has a competitive advantage.

“The value of a financial planner goes beyond investment management and is a dynamic, iterative, and ongoing process,” says Brett Koeppel, CFP and Founder of Eudaimonia Wealth. “Until artificial intelligence can empathize and connect on a human level, its value will remain limited to the technical aspects of financial advice.”

“Human advisors can maintain relevance by offering personalized, empathetic guidance that AI cannot replicate and by integrating AI tools into their services to enhance their value proposition,” says Bernstein. “We should also stay abreast of other disruptions like blockchain and fintech innovations, which could further transform the industry.”

Human advisors must also act as bots’ stewards as they delve deeper into business practices. Effectively delineating tasks and responsibilities is critical.

There may be chief concerns surrounding regulatory compliance and the complex liability issue. When technology-driven decisions fail, who is accountable when an automated system makes an error – the adviser, the technology provider, or the wealth management firm?

As AI rapidly integrates into the financial advisory industry, it promises to revolutionize investment management by making sophisticated tools accessible to all investors. However, not all advisors are worried. They see the human touch as indispensable to their craft. Advisors who effectively offer empathy, nuanced guidance, and support through complex life events will retain an advantage in this new age of generative AI content.

Yet advisors must also embrace AI tech’s power to automate monotonous admin tasks and achieve the analytical edge for forecasting and accounting. Tomorrow’s advisors will effectively leverage AI for technical aspects of the job for more time and energy to focus on delivering interpersonal coaching that only a human can.

This article was produced by Media Decision and syndicated by Wealth of Geeks.

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