Researchers at Chalmers University of Technology in Sweden say that if an electric car charges while driving, the size of the battery can be reduced by up to 70 per cent.

Aim Of The Study? 

The aim of the Chalmers University study was to discover what potential benefits there might be with a so-called electric road system (ERS) where cars charge while driving.

What Is An ERS? 

An electric road system (ERS) is a transportation infrastructure that allows electric vehicles (EVs) to charge their batteries while driving on the road. The technology works by installing conductive materials, such as overhead cables or conductive strips, on the road surface that are connected to an electricity grid. These materials can transfer power to electric vehicles fitted with special equipment, such as a pantograph, which collects the energy and charges the vehicle’s battery.

ERS technology has the potential to significantly reduce the need for large batteries and charging infrastructure, making EVs more practical for long-distance travel. The system can also help to reduce carbon emissions from transportation by promoting the use of electric vehicles. Several countries, including Sweden and Germany, have already begun testing ERS technology on highways and major roads.

The Data 

For the study, the researchers combined the so-called electric road system with real-life driving patterns of Swedish drivers and used data from over 400 passenger cars to study real driving patterns on different parts of Swedish national and European roads.

The data was used to calculate, among other things, the battery size needed to complete all journeys given possible charging options i.e., stationary versus electric road system (ERS), charging patterns, and total costs including infrastructure and batteries.

The Optimal Situation 

The researchers concluded that a combination of electric roads on 25 per cent of the busiest national and European roads, and home charging would be the optimal level that would enable batteries to become significantly smaller, at best only one-third of the current size.

What Would This Mean For Motorists? 

As pointed out by Sten Karlsson, one of the researchers behind the study, “We see that it is possible to reduce the required range of batteries by more than two thirds if you combine charging in this way. This would reduce the need for raw materials for batteries, and an electric car could also become cheaper for the consumer.”  The researchers found that the net savings for the car owner from smaller batteries would exceed the cost of the electric road system (ERS).

Also, peaks in electricity consumption could be reduced if car drivers didn’t entirely rely on home charging i.e., charging more evenly throughout the day would mean that peak load would be significantly reduced.

It Depends Where You Live 

Researchers also discovered, however, that that there are major differences between groups, depending on driving patterns and proximity to electric roads. Even in the optimal case, some would manage with only electric road charging, while others, such as those who live in sparsely populated areas would not be able to use the opportunity at all. For example, researcher Wasim Shoman said: “those who live in the countryside would need almost 20 per cent greater range on their batteries compared to those who live in a city centre”. 

What Does This Mean For Your Organisation? 

Although there have been some trials, there is no operational electric road system (ERS) in the UK as yet, there were only 38982 public electric vehicle charging points across the UK by the end of February (Zap Map), and most homes don’t have their own electric vehicle charging points. This means that although the research shows that a combination of home charging and ERS could bring down the battery size and make electric cars cheaper to buy and put less of a strain on the grid at certain times, this situation is still some way off. The more electric cars and the closer the UK can move toward a functional ERS, the more chance it has of decarbonising transportation which would benefit all and help the UK meet its green targets.

Microsoft Is Founded

Bill Gates originally wanted to become a lawyer, like his father, when he was a young child.

However, as he grew up he discovered computers and on this week in history (4th April back in 1975) he, along with his school-friend Paul Allen founded “Micro-Soft” as it was called back then. Whilst they coding in BASIC for little projects, their big break came when Bill used a little cunning ploy to ascertain a market opportunity. He reached out to Micro Instrumentation and Telemetry Systems (MITS) and let them believe that a number of people were writing code for their Altair 8800 microprocessor machine and suggested they could have a demonstration of it if they wanted.

The clever/cunning/devious part was that there was no BASIC written for the machine at that time and Gates was simply fishing to ascertain any appetite they may have. Upon being granted an interview/demonstration-opportunity, he then frantically organised getting the code written for an Altair emulator in time to impress MITS for the fateful demonstration … then got a deal that started them on their meteoric journey.

Since then, Microsoft has acquired a total of 213 companies, with 39 of those acquisitions taking place within the past five years alone and Bill Gates now has a net worth of over $110 Billion dollars, despite not working full-time at Microsoft for quite some time and concentrating more and more time with other issues and philanthropic works (depending on what/whom you believe).

The moral of the story? It’s a good idea to test you have a hungry market first before you build the product. It can also be good idea to outsource the production (e.g. coding) to allow yourself time to rapidly build your business …

Gordon Moore, the co-founder of Intel Corp, predictor of home computing, and the creator of ‘Moore’s Law’ has died at the age of 94.

Intel Corporation

In July 1968, Gordon Moore famously co-founded Intel Corporation with Robert Noyce, who had previously co-founded Fairchild Semiconductor. Moore saw an opportunity to create a new company focused on the production of memory chips for computers.

Moore and Noyce had worked together at Fairchild Semiconductor, where they had made significant advances in the design and production of microchips but left to found Intel with the goal of producing high-quality, reliable memory chips that could meet the growing demand for computer memory.

At the time, the semiconductor industry was still in its infancy, and many believed that it would be dominated by large corporations such as IBM. However, Intel quickly established itself as a major player in the industry, thanks in part to the development of the world’s first commercially available microprocessor in 1971.

Acknowledged 

Today, Intel is one of the world’s largest and most influential technology companies, producing a wide range of microprocessors, memory chips, and other computer components that are used in everything from personal computers to data centres to autonomous vehicles. Following the news of his death, Intel Corp acknowledged Moore’s contribution as the co-founder of its company and as a tech industry pioneer by saying in a tweet, “Today, we lost a visionary. Gordon Moore, thank you for everything.” 

Moore’s Law 

Back in 1965, in an article for Electronics magazine, Moore observed that the number of transistors on a microchip was doubling approximately every year and predicted that this trend would continue for at least another decade. This prediction, later known as “Moore’s Law,” has proven remarkably accurate, with the number of transistors on a microchip continuing to double every 18-24 months.

As a result of this trend, the cost of computing power has decreased exponentially, making it possible for personal computers to become affordable and accessible to a wide range of people. Moore’s insight into the future of computing power and cost laid the groundwork for the home computing revolution which began in the 70s and 80s.

Medal of Freedom 

In 2002, Gordon Moore received the Presidential Medal of Freedom in 1990 from President George H.W. Bush for his contributions to the field of computer technology. The Medal of Freedom is the highest civilian award in the United States and is awarded to individuals who have made significant contributions to the security or national interests of the United States, to world peace, or to cultural or other significant public or private endeavours.

Moore was recognised for his role in founding Intel Corporation and for his contributions to the development of the microprocessor, which has revolutionised the field of computing and had a profound impact on modern society.

Philanthropist and More 

In addition to his work at Intel, Moore has been a prominent philanthropist and supporter of education and scientific research, particularly in the fields of environmental conservation and the life sciences.

For example, in the 1990s, Moore was involved in efforts to conserve tropical forests in Indonesia, which were under threat from logging and other forms of development. Working with local communities and conservation organisations, Moore supported efforts to establish protected areas and sustainable forestry practices in the region.

Also, in 2000, Moore and his wife founded the Gordon and Betty Moore Foundation, which is dedicated to advancing environmental conservation, scientific research and patient care. One of the Foundation’s signature initiatives is the Marine Conservation Initiative, which supports efforts to protect and restore the health of the world’s oceans.

What Does This Mean For Your Business? 

Gordon Moore is widely accepted to be a visionary and pioneer in the field of technology who not only founded one of the most successful and influential technology companies in the world, but whose work and predictions laid the groundwork for the home computing revolution. The computer and semiconductor technology that he helped develop completely changed how businesses operate and is still central to the technology industry in the digital age that businesses now operate in.

Moore’s Law has proven to be remarkably accurate and has had a huge influence on  business technology, for example by enabling businesses to perform more complex computations, process larger amounts of data, and run more sophisticated software applications. Miniaturisation lead to more portable and convenient devices (and the industries built-around them) with lower costs from more computing equipment due to economies of scale in microchip production. Also, the increasing computing power enabled by Moore’s Law has also played a crucial role in the development of artificial intelligence and machine learning technologies. These technologies have the potential to transform many industries, from healthcare to finance to transportation, and are expected to become increasingly important in the years to come.

It should also be remembered that Moore’ philanthropic, environmental conservation and scientific research work have had a significant impact on society and the business world, helping to promote sustainability, advance knowledge, and improve the quality of life for people around the world.

Conversational chatbot ChatGPT’s creators OpenAI have announced that ChatGPT will now be able to use plugins to improve its capabilities and outputs.

Plugins Coming To ChatGPT 

It’s been announced that  OpenAI will be “gradually” enabling ChatGPT to use plugins for certain groups of ChatGPT users to begin with, starting with ChatGPT Plus subscribers. It’s also beginning to roll out the ability for developers to create their own plugins and enable developers using OpenAI models to integrate plugins into their own applications beyond ChatGPT.

Browse The Web To Access New Information + Python

Crucially, ChatGPT will be able to use a web browsing plugin so it can access the Internet and read information (using the Bing search API) which will enable it to expand the amount of content it can discuss, and use “fresh information from the present day”. 

Also, OpenAI says that it has a plugin for Python code execution (a code interpreter plugin), which it says is “amazing for data science use-cases”. Python code is a set of instructions or commands written in the Python programming language, which is widely used for various applications, including web development, data analysis, artificial intelligence, and scientific computing. Normally Python code can be written in a text editor or an integrated development environment (IDE) and saved with a .py extension.

Why? 

OpenAI says that although language models like ChatGPT are impressive they are currently limited by the fact that the only information they can learn from is their training data which can be out-of-date, and that this data is one-size-fits-all across applications. This is because ChatGPT was only trained on data up until September 2021, so can’t retrieve information based on the latest news, data, and developments or proprietary sources.

Also, the only thing language models can do “out-of-the-box” is emitting text which can give useful instructions. However, to follow the instructions, users need ChatGPT to have another process in place.

How Plugins Can Help 

OpenAI says that plugins can, therefore, act as the “eyes and ears” for language models and give them access to information that is more recent, personal, and specific than the data that was used to train them.

Examples of how certain plugins will be used to improve the outputs of ChatGPT for users include:

– A web browser plugin, hosted by OpenAI, which allows ChatGPT to read current information from the Internet. This means that users can generate up-to-date outputs. Also, the browser plugin shows which websites were visited and cites its sources in ChatGPT’s responses, thereby giving transparency and helping users to verify the accuracy of the model’s responses.

– An open-source retrieval plugin to enable ChatGPT to access personal or organisational information sources (with permission). This means that ChatGPT users will be able to obtain the most relevant document snippets and data sources, such as files, notes, emails, or public documentation.

– Third-party plugins, created by developers for ChatGPT, e.g. Expedia, FiscalNote, Instacart, KAYAK, Klarna, Milo, OpenTable, Shopify, Slack, Speak, Wolfram, and Zapier. This will enable access to third-party services, widening the scope of ChatGPT even further.

Safety Considered 

OpenAI has made it very clear in its announcement about the impending introduction of plugins that security has been a major consideration. For example, OpenAI says it has performed “red-teaming exercises” to reveal potential risks from plugin integrations. OpenAI also says it’s using the findings from these exercises to inform safety-by-design mitigations that restrict risky plugin behaviours and improve transparency. Safety considerations are also reported to be behind the decision to gradually deploy access to plugins rather than introduce them to all user groups immediately.

What Does This Mean For Your Business? 

Integrating plugins is another huge step forward in that it will add even more value to ChatGPT by enabling it to overcome one of its more obvious limitations – the fact that it was only trained up until September 2021. This has meant that it hasn’t been able to access and use up-to-date information, until now. By integrating explicit access to external data via plugins, such as up-to-date information online, code-based calculations, or custom plugin-retrieved information, this will enable users to get even more value from ChatGPT. It also opens up more opportunities for developers and for those using the chatbot for data and science purposes. Coupled with the introduction of GPT-4, the integration of plugins is the next step forward in the rapid rise of ChatGPT becoming one of the world’s most advanced and widely use language models that offers almost endless opportunities to businesses and is proving to be a significant time and money-saver.

In this article, we look at how generative AI could change work and jobs going forwards, plus how it could help businesses adopt new work trends such as a 4-day week.

The Rise Of Artificial Intelligence (AI) – A Timeline 

AI has been many decades in the making. For example, the field of AI was established with a summer workshop at Dartmouth College in 1956, the first AI program, called “The General Problem Solver,” was developed in 1959, and the concept of “machine learning” was introduced in 1966 by (Arthur Samuel). That said, it wasn’t really until 1980s that the field of neural networks was established (machine learning inspired by the human brain) and, of course, with the rise of the internet in the 90s that AI techniques actually started to be used by search engines, leading to better helping users find information and products online.

Some of the most notable developments of AI (up until the more recent advent of the introduction of ‘generative AI’ heralded by the arrival of OpenAI’s ChatGPT) include:

2011: IBM’s Watson defeats human champions on the quiz show Jeopardy! using natural language processing and machine learning.

2014: Google’s DeepMind creates an AI system that can play Atari video games at a superhuman level.

2015: Amazon introduces the AI-powered voice assistant Alexa, which can perform tasks and answer questions using natural language input.

2016: Google’s AlphaGo defeats the world champion in the game of Go, which was previously considered too complex for computers to play at a high level.

2017: The first self-driving cars become available to the public, using AI to navigate and make decisions on the road.

2020: The COVID-19 pandemic leads to increased adoption of AI in healthcare, including the usage of machine learning to analyse medical images and predict the spread of the virus.

How Are Businesses Already Using AI ?

Businesses are already using AI as part of their work in a variety of ways, including:

– Customer service. Chatbots and virtual assistants can provide customers with quick and efficient service, handling routine tasks and answering common questions.

– Marketing. AI can analyse data to identify patterns and preferences among customers, allowing businesses to create more targeted and personalized marketing campaigns.

– Operations. AI is already being used to optimise supply chain management, inventory control and production processes, leading to cost savings and increased efficiency.

– Fraud detection. AI can analyse data to identify potential instances of fraud or financial misconduct, helping businesses prevent losses and maintain compliance.

– Predictive analytics. AI can be used to make predictions about future trends or events, such as sales forecasts or risk assessments, allowing businesses to make better-informed decisions.

– Overall, AI has already become a valuable tool for businesses across a wide range of industries, offering the potential for increased efficiency, cost savings, and competitive advantage.

Generative AI : A Game-Changer For Businesses 

Although AI has been gradually introduced into many aspects of our lives and work in recent years, the biggest and most notable splash has come from the introduction of generative, conversational AI Large Language Model (LLM) chatbots like ChatGPT. With ChatGPT’s GPT-3.5 architecture due to upgraded with new image features soon with GPT-4, with ChatGPT soon to have a web browsing plugin, plus with the integration of the ‘Copilot’ chatbot with Microsoft 365 and Google’s ‘Bard’ conversational chatbot on the way, generative AI is about to play an even bigger role in our lives and work.

How Important Will Generative AI Be To Businesses? 

A recent Salesforce survey of 500 senior IT business leaders gives an idea of the perceived value of generative AI to businesses going forward. The survey showed that the majority (67 per cent) of business leaders are now prioritising generative AI for their business within the next 18 months, with one-third (33 per cent) naming it as a top priority.

How Might Generative AI Affect Jobs In The Future? 

With businesses giving (and planning to give) greater priority to generative AI, this has the potential to create a wide range of new jobs in the future, thereby changing the jobs market. Some possible examples of jobs that generative AI may create include:

– AI trainers. These individuals would be responsible for training the AI algorithms to generate specific outputs that meet certain criteria, such as realistic images or natural-sounding speech.

– AI data specialists. These individuals would be responsible for collecting and analysing data that is used to train generative AI models. They would also be responsible for ensuring that the data is high quality and diverse enough to produce accurate and unbiased results.

– AI art curators. As generative AI continues to advance in the realm of art and creative expression, there will likely be a need for individuals who can curate and showcase AI-generated artwork in galleries and museums.

– AI content creators. As AI-generated content becomes more common, there will be a need for individuals who can write scripts or create storyboards that guide the generative AI algorithms towards specific outcomes. This is already a role that many existing content creators are having to adapt to.

– AI ethicists. As AI continues to advance, there will be a growing need for individuals who can assess and address the ethical implications of generative AI. They would be responsible for ensuring that the AI algorithms are transparent, fair and unbiased.

– AI translators. As generative AI algorithms become more advanced, there may be a need for individuals who can translate the output of one algorithm into a format that can be understood by another algorithm. Alternatively, this may be done by AI itself.

– AI analysts. These individuals would be responsible for analysing the output of generative AI algorithms to determine their effectiveness and identify areas for improvement.

Overall, the possibilities for new jobs in generative AI are vast and varied and will likely continue to expand and change as the technology continues to evolve. It is likely too that as generative AI creates new jobs, as it improves its capabilities, it may swallow up those new jobs too!

How Will Generative AI Affect Human Workers? 

The increasing use of generative AI and improvements in the technology landscape are likely to reshape the job market and require workers to continually adapt and develop new skills. However, there will also be new opportunities for workers who are able to leverage the power of AI and develop expertise in the technology.

The 4 Day Week And AI 

It has long been predicted that greater automation and technological advances will lead to shorter working weeks. For example, in the 1930s, economist John Maynard Keynes predicted that technological advancements would lead to a 15-hour work week.

With this in mind, the results of the world’s largest four-day working week pilot (Autonomy for 4 Day Week Global) were recently published. The study, which took place in the UK from June to December 2022, involved 61 companies in diverse sectors and sizes, and around 2,900 workers. The results were overwhelmingly positive with 56 of the 61 companies who took part continuing with the four-day week (92 per cent), and 18 confirming the policy is a permanent change. The ‘Before and after’ data showed that 39 per cent of employees were less stressed, and 71 per cent had reduced levels of burnout at the end of the trial. Also, measures of work-life balance were found to have improved across the trial period.

How Could Generative AI Contribute To Making A 4-Day Week Achievable For Businesses? 

The concept of a 4-day workweek has gained momentum in recent years, with businesses exploring ways to improve work-life balance and productivity.

Generative AI is an emerging technology with the potential to transform various industries and could play a key role in making the 4-day workweek a reality.

By automating repetitive tasks such as data entry and administrative work, generative AI can free up employees’ time to focus on more complex and strategic work. This could increase productivity and efficiency, potentially allowing for a shorter workweek.

Generative AI can also analyse vast amounts of data and provide insights to inform decision-making, enabling businesses to make more informed decisions in less time. Additionally, generative AI can be used to develop chatbots and other automated customer service tools, providing 24/7 customer support without requiring employees to work longer hours.

Also, by providing tools for virtual collaboration, project management, and communication, generative AI can help businesses to create more flexible work environments that can accommodate a 4-day workweek.

The adoption of generative AI, therefore, has the potential to revolutionise the way businesses operate and create a more balanced and productive work culture.

It Will Take Work & Planning Plus Will Require Cultural Change 

Overall, by leveraging the power of generative AI, businesses can become more efficient and productive, potentially allowing for a shorter workweek without sacrificing performance or profitability. However, it’s important to note that the adoption of generative AI also requires careful planning, training, management, and cultural change to ensure that it is implemented effectively and ethically.

What Does This Mean For Your Business? 

The increased productivity, time and cost savings that generative AI is already delivering to businesses are a taster of the potential going forward as the technology improves. It’s clear that generative AI is changing existing jobs and will create new job opportunities and roles as businesses give the technology greater priority. The benefits of generative AI also have the potential to help businesses adopt new work trends, such as the 4-day week and, just as predicted over the years, the automation created by technology could see people spending much less time engaged in ‘work’ and able to achieve a better work/life balance. Businesses, however, will have to engage in more planning and manage cultural change to help them adapt to make the most of the opportunities that generative AI provides.