The recently launched Pyxis Ocean cargo ship uses giant foldaway ‘WindWings’ to help supplement engine power and could cut lifetime carbon emissions by 30 per cent.

The Cargo Ship 

The A Mitsubishi Corporation cargo ship, is currently demonstrating the WindWings, developed by BAR Technologies and Yara Marine Technologies, during its six week-long maiden voyage from China to Brazil. The ship, chartered by Cargill Ocean Transportation, left from Singapore on 25 August carrying 81,000 tonnes of cargo.

The WindWings 

The extraordinary features of the Pyxis Ocean cargo ship are its two rigid, foldaway 37.5-metre-tall steel and fibreglass ‘sails’ (WindWings) which automatically pivot to catch the wind. The WindWings, each made up of a centrally pivoted 10-metre-wide section with two five-metre-wide wings on either side can be folded down onto the cargo ship’s deck for arrival at ports and for passing through bridges or canals.

BAR Technologies estimates that the wind power harnessed by the WindWings, which can be retrofitted to many cargo ships (but not container ships), could deliver an average fuel saving of up to 30 per cent (on new build ships) and could save as much 1.5 tonnes of fuel per day on an average global route. Adding four wings on cargo could, therefore, save a massive 6 tonnes of fuel per day, stopping 20 tonnes of CO2 being produced.  BAR Technologies says the WindWings make the savings by combining “wind propulsion with route optimisation” and are initially aimed at being fitted to “bulk carriers and tankers.” 

Targets 

With more than 90 per cent of world trade being carried across oceans by 90,000 fossil-fuel powered marine vessels, the global freight shipping industry is a major producer on CO2 emissions, which contribute to climate change (and acidification). For example, it’s been estimated that the global shipping industry is responsible for more than 3 per cent of global CO2 emissions and, if it were a country, it would be the sixth largest producer of greenhouse gas (GHG) emissions.

For these reasons, the International Maritime Organisation (IMO) set the goal for the shipping industry ultimately arriving at a 50 per cent reduction in GHG emissions from 2008 levels (CO2, sulphur oxide and other gasses) by 2050.

Adding WindWings to cargo ships could, therefore, be one relatively fast way, in the absence of zero-carbon fuel for ships or a clear decarbonisation strategy, to at least begin reducing GHG emissions.

Innovation 

John Cooper, Chief Executive Officer, BAR Technologies said of the WindWings: “If international shipping is to achieve its ambition of reducing CO2 emissions, then innovation must come to the fore. Wind is a near marginal cost-free fuel and the opportunity for reducing emissions, alongside significant efficiency gains in vessel operating costs, is substantial.” 

What Does This Mean For Your Organisation?

When the alarm bells really started ringing back in 2008 about how the global shipping industry was producing more CO2 than most countries, twice as much as the air transport industry, and more than 3 per cent of global emissions, the ambitious but necessary 50 per cent cut by 2050 target was set. However, with the world still reliant on cargo ships for 90 per cent of international trade, no zero-emissions fuel on the horizon, a perceived relative inactivity among freight operators in trying to meet the target, and no clear strategy, the WindWings idea looks like a realistic option to get started. Although there’s ‘no one fits all’ and it may not work for container ships, they have been designed to be workable on the most common vessels sizes (using either 3 or 4 WindWings). The fact that they’re fully automated (touch of a button), can be folded away, have a lower power consumption and yet have the capacity to make major fuel and CO2 emission savings mean that, as long as they are affordable and reliable, they could provide a practical, and sustainable way forward for the freight shipping industry until other options are available. There’s also a kind of irony to the idea that the leading technology of today for greener shipping takes ships back full circle to the days of sails, with these just being more high-tech versions – an old solution to a newer problem.

28 Years Ago : eBay (& Amazon by Comparison)

Whilst eBay’s market cap is dwarfed by that of Amazon (i.e. circa 24 billion dollars compared to circa 1.4 trillion dollars), it’s easy to forget eBay helped shape online purchasing too.

Before it was rebranded as eBay in 1997, the site was originally called AuctionWeb. Founded by Pierre Omidyar in 1995, it was an experiment to create an online venue for person-to-person auctions and lacked any heavy investment. In fact, the hosting company were just charging thirty dollars per month to for the entire website when he started up, until they said they’d no longer host it for that price due to the growth in traffic, thereby forcing him to monetise his website via his sellers, which worked.

With his degree in computer science behind him and having worked in a subsidiary company of Apple, he was also working on various other web projects. He’d also co-founded another company called Ink Development, a company initially focused on developing software for pen-based computing. The company transformed its direction and became an e-commerce platform named eShop, which was later acquired by Microsoft in 1996.

In short, Pierre was the right person in the right place at the right time. And so was Elon Musk (more on him later).

The Unexpected First Listing

The first item ever listed on AuctionWeb was a laser pointer. To be more precise, it was a broken laser pointer. This wasn’t a mistake or an oversight. Omidyar had bought it for his own use but found out it was faulty. Rather than discarding it, he decided it would make an interesting first listing on his experimental auction site. He listed it clearly mentioning it was non-functional. To his astonishment, the laser pointer garnered bids and finally sold for $14.83.

Intrigued by someone paying for a known broken item, Pierre out to the buyer who simply responded that he was a collector of broken laser pointers. This quirky initial transaction showed the potential of a vast, unpredictable, and diverse online marketplace.

The Beanie Baby Phenomenon

While the broken laser pointer was AuctionWeb’s first sale, it was the Beanie Baby craze in the mid-90s that truly skyrocketed the platform’s popularity. Beanie Babies, those small plush animals filled with plastic pellets, became a massive collector’s item. AuctionWeb became a primary marketplace for these avid collectors, providing them a platform to buy, sell, and trade these toys.

The Beanie Baby phenomenon showcased the strength of the platform in bringing together niche audiences globally and the success also signalled the beginning of a new era where the average person could become an entrepreneur from the comfort of their own home.

From AuctionWeb to eBay

Seeing the growing potential, Omidyar soon renamed AuctionWeb to “eBay,” which was short for Echo Bay, the name of Omidyar’s consulting firm. The rest is history! eBay went public on September 24, 1998.

On its first day of trading, the stock’s price of $53.50 soared well past the initial target of $18, emphasising the optimism investors held during the dot-com boom. Unlike many that fell by the wayside, eBay is now a business that operates in over 30 countries with a market cap peaking at 80.6 billion dollars.

Amazon and eBay – Different Approaches.

While eBay and Amazon both started as online marketplaces in the 1990s, they evolved with different business models and strategies that have influenced their trajectories. eBay started off as an online auction place, although plenty of people and businesses sell via their ‘Buy Now’ function as an online shop.

There are many possibilities as to why eBay hasn’t reached the same magnitude as Amazon and here are a few :

1. Business Model: eBay began as a peer-to-peer auction site, allowing individual sellers and buyers to negotiate prices. This gave eBay a unique identity but also meant slower and less predictable transactions. Amazon, on the other hand, started as a book retailer and then expanded its product range, focusing on selling new products at fixed prices.
2. Fulfilment and Logistics: Amazon invested heavily in fulfilment-centres and logistics, creating a vast and efficient infrastructure for storage, packing, and shipping. This allowed them to ensure rapid delivery, leading to services like Amazon Prime. eBay, on the other hand, relies on individual sellers to handle shipping and logistics, which can be more variable in terms of speed and reliability.
3. Private Label & Product Expansion: Amazon developed its own private-label products and expanded into diverse categories. They also encouraged third-party sellers to use their platform, ensuring a vast product range.
4. Ecosystem Development: Amazon diversified its business areas, venturing into hardware (Kindle, Echo), streaming (Amazon Prime Video), cloud services (AWS), and more. This diversification created multiple revenue streams and bolstered its market presence.
5. Trust and Reliability: Amazon’s emphasis on customer service and consistent delivery times built significant trust with customers. While eBay has made efforts to ensure product authenticity and seller reliability, the peer-to-peer model sometimes leads to inconsistencies in product quality and delivery.
6. Global Expansion Strategy: Both companies pursued international expansion, but Amazon’s aggressive strategy of setting up localized versions of its site, fulfilment centres, and tailored services for different countries gave it a strong global footprint.
7. Subscription Model: Amazon Prime, a subscription-based service, not only offers faster delivery but also includes streaming, exclusive deals, and other perks. This has fostered customer loyalty and increased purchase frequency.
8. Feedback System: While eBay’s feedback system was innovative and built trust in the early days, some argue that it’s become less effective over time due to potential biases and reluctance from buyers and sellers to leave negative feedback.
9. Acquisitions and Divestitures: While both companies made acquisitions, their strategies differed. Amazon’s acquisitions like Zappos, Whole Foods, and Twitch were integrated into its ecosystem. eBay, on the other hand, made some large acquisitions, such as Skype (see below), which were later divested as they didn’t align with eBay’s core focus.

What can be seen is that eBay seems to have plateaued insofar as the gross merchandise volume (GMV) (i.e. the total amount of ‘stuff’ sold via the platform) is concerned whereas Amazon’s GMV is steadily rising and so is the share of that GMV being sold by third party sellers (rather than Amazon directly) so doubtless they’re eating some of eBay’s lunch.

Perhaps the different share prices reflect the differing optimism because if there’s one thing that investors like, it’s growth.. One thing that’s clear … both companies did well over the pandemic.

While eBay didn’t reach the same dizzying heights of Amazon, it’s nevertheless a true rags-to-riches success-story that’s worth studying, including a couple of their better-known acquisitions. Even if the acquisitions were later sold, it’s interesting to try and appreciate the thinking behind the strategy and synergy.

Payment Provider : X Marks The Spot

The X Factor Elon Musk’s wealth originated from a critical acquisition made by eBay in 2002. In the late 1990s, Musk co-founded X.com, an online payment company. X.com would later become known as PayPal after a series of developments and a merger.

It was this very company, PayPal, that eBay acquired in 2002 for $1.5 billion in stock. At the time of the acquisition, Musk held 11.7% of PayPal shares, translating to roughly $165 million from the sale. Not too shabby for Mr Musk and it certainly helped springboard his wealth to be in the same league as that of Jeff Bezos from Amazon.

Communications Considerations : Skype

In late 2009, eBay finalized the sale of Skype for an impressive $2.75 billion. This strategic move allowed eBay to refocus on its core e-commerce operations, while the deal also highlighted Skype’s significant growth and potential in the telecommunications sector.

The Future?

Whilst Amazon seems intent on taking over the world by expanding relentlessly into eBay’s territory (and many others), eBay will likely remain a trusted corner-of-the-web for people to buy and sell goods for many years to come.

All of which started 28 years ago (this week), with a good idea and a broken laser-pointer.

If you’d like to backup your ChatGPT chats, it’s possible to export them by email from within ChatGPT. Here’s how:

– In ChatGPT, click on the three dots (bottom left).

– Click on ‘Settings & Beta.’

– Click on ‘Data Controls.

– Click on the ‘Export Data’ button, read the information, and click on ‘Confirm export’ (if you agree).

– The data will be sent to your registered email in a downloadable file and will include account details and conversations.

In this article, we look at why Zoom found itself as the subject of a backlash over an online update to its terms related to AI, what its response has been, plus what this says about how businesses feel about AI.

What Happened? 

Communications app Zoom updated its terms of service in March but following the change only being publicised on a popular forum in recent weeks, Zoom has faced criticism because many tech commentators have expressed alarm that the change appeared to go against its policy to not use customer-data to train AI.

The Update In Question 

The update to Section 10 of is terms of service, which Zoom says was to explain “how we use and who owns the various forms of content across our platform” gave Zoom “perpetual, worldwide, non-exclusive, royalty-free, sublicensable, and transferable license and all other rights” to use Customer Content, i.e. data, content, communications, messages, files, documents and more, for “machine learning, artificial intelligence, training, testing” (and other product development purposes).

The Reaction 

Following the details of the update being posted and discussed on the ‘Hacker News’ forum, there was a backlash against Zoom, with many commentators unhappy with the prospect of AI (e.g. generative AI chatbots, AI image generators and Zoom’s own AI models namely Zoom IQ) and more) being given access to what should be private Zoom calls and other communications.

What’s The Problem? 

There are several concerns that individuals, businesses and other organisations may have over their “Customer Content” being used to train AI. For example:

– Privacy Concerns – worries that personal or sensitive information in video calls could be used in ways the participants never intended.

– Potential security risks. For example, if Zoom stores video and audio data for AI training, it increases the chance of that data being exposed in a hack or breach. Also, it’s possible with generative AI models that private information could be revealed if a user of an AI chatbot asked the right questions.

– Ethical questions. This is because some users may simply not have given clear permission for their data to be used for AI training, raising issues of consent and fairness.

– Legal Issues. For example, depending on the country, using customer data in this manner might violate data protection laws like GDPR, which could get both the company and users into legal trouble. Also, Zoom users or admins for business accounts could click “OK” to the terms of service without fully realising what they’re agreeing, to and employees who use the business Zoom account may be unaware of the choice their employer has made on their behalf. It’s also been noted by some online commentators that Zoom’s terms of service still permit it to collect a lot of data without consent, e.g. what’s grouped under the term ‘Service Generated Data.’

Another Update Prompted 

The backlash, the criticism of Zoom and the doubtless fear of some users leaving the platform over this controversy appears to have prompted another update to the company’s terms of service which Zoom says was to “to reorganise Section 10 and make it easier to understand”. 

The second update was a sentence, in bold, added on the end of Section 10.2 saying: “Zoom does not use any of your audio, video, chat, screen sharing, attachments or other communications-like Customer Content (such as poll results, whiteboard and reactions) to train Zoom or third-party artificial intelligence models.” 

On the company’s blog, Chief Product Officer, Smita Hashim, re-iterated that: “Following feedback received regarding Zoom’s recently updated terms of service Zoom has updated our terms of service and the below blog post to make it clear that Zoom does not use any of your audio, video, chat, screen sharing, attachments, or other communications like customer content (such as poll results, whiteboard, and reactions) to train Zoom’s or third-party artificial intelligence models.” 

The Online Terms of Service Don’t Affect Large Paying Customers 

Smita Hashim explains in the blog post that the terms of service typically cover online customers, but “different contracts exist for customers that buy directly from us” such as “enterprises and customers in regulated verticals like education and healthcare.” Hashim states, therefore, that “updates to the online terms of service do not impact these customers.” 

What Zoom AI? 

Zoom has recently introduced two generative AI features to its platform – Zoom IQ Meeting Summary and Zoom IQ Team Chat Compose, available on free trial and offering automated meeting summaries and AI-powered chat composition.

To customers worried that these tools may be trained using ‘Customer Content’ Zoom says, “We inform you and your meeting participants when Zoom’s generative AI services are in use” and has specifically assured customers that Zoom does not use customer content (e.g. as poll results, whiteboard-content, or user-reactions) to train Zoom’s own (or third-party) AI models.

Criticism 

In 2020, Zoom faced criticism over only offering end-to-end encryption as a paid extra feature after saying paying users would have it anyway. Also, with Zoom being the company whose product enabled (and is all about) remote working, it was criticised after asking staff living within a “commutable distance” (i.e. 50 miles / 80km) of the company’s offices to come to the office twice a week when it was reported to have said (at one time) that all staff could work remotely indefinitely.

What Does This Mean For Your Business? 

This story shows how, at a time when data is now needed in vast quantities to train AI, a technology that’s growing at a frightening rate (and has been the subject of dire warnings about the threats it could cause), clear data protections in this area are lagging or are missing altogether.

Yes, there are data protection laws. Arguably however, with the lack of understanding of how AI models work and what they need, service terms may not give a clear picture of what’s being consented to (or not) when using AI. There’s a worry, therefore, that boundaries of data protection, privacy, security, ethics, legality, and other contraints may be overstepped without users knowing it in the rush for more data as clear regulation is left behind.

Zoom’s extra assurances may have gone some way toward calming the backlash down and assuring users, but the fact that there was such a backlash over the contents of an old update shows the level of confusion and mistrust around this relatively new technological development and how it could affect everyone.

Following the announcement that Microsoft is releasing a public preview of Python in Excel, we look at what this will mean for Excel users and how it could help businesses.

What Is Python? 

The initial version was created in the late 1980s by Guido van Rossum, with its first official release, Python 0.9.0, coming out in February 1991. It was named after the eponymous Monty Python Show, after having been developed as a successor to the ABC language and was intended to be easy to read and allow for concise code, among other goals.

It’s regarded as a good general-purpose programming language that’s relatively easy to learn due to its simple and straightforward syntax. Python is often used in creating web applications and artificial intelligence applications, and it is the language behind platforms like Pinterest and Instagram.

Added To Excel 

Last week, Microsoft announced that is releasing a Public Preview of Python in Excel, thereby enabling the combination of Python and Excel analytics within the same workbook, with no setup required. Microsoft says: “With Python in Excel, you can type Python directly into a cell, the Python calculations run in the Microsoft Cloud, and your results are returned to the worksheet, including plots and visualisations.”  In short, this means that Excel users will be able to carry out advanced data analysis in the familiar Excel environment, by accessing Python from the Excel ribbon.

Two other key benefits of the integration highlighted by Microsoft are that it runs securely on the Microsoft Cloud, thereby keeping data private, and it is built to work with Teams. This enables colleagues to (seamlessly) interact with and refresh Python in Excel based analytics without needing to worry about installing additional tools, Python runtimes, or managing libraries and dependencies.

What Sort Of Things Can Be Done With The Excel/Python Combination?

Python’s ability to manipulate Excel tables will be of particular help to businesses that frequently work with data because it offers many practical benefits and uses. For example:

– Saving time by automating repetitive tasks in excel, e.g. formatting, or reorganising data.

– Potentially getting better data insights because Python enables the handling of large data sets and can be more efficient in processing and analysing that data.

– Saving time and doing a better job of data cleaning, e.g. Python is better at locating missing values, standardising formats, removing duplicates, and using techniques like regular expressions for pattern-based transformations.

– Improved data analysis and analytics due to the use of Python’s powerful data analysis libraries, e.g. Pandas, Matplotlib, and scikit-learn and the fact that Python in Excel leverages Anaconda (a popular enterprise repository) Distribution for Python running in Azure. This can help with complex calculations, statistical analysis, and data transformations that might be cumbersome or inefficient in Excel.

– Advanced visualisation. I.e., Python charting libraries like Matplotlib and seaborn enabling the creation of a wide variety of charts, spanning from conventional bar graphs and line plots to more specialized visualisations such as heatmaps, violin plots, and swarm plots.

– Helping to focus collaborative work efforts, e.g. where multiple people or systems are providing data in different formats or structures, Python acts as an aggregator, harmonising and consolidating diverse data sources into a single Excel sheet or structure.

– Python scripts can be scheduled to run at specified intervals, thereby making it easier to update or analyse Excel data even when you’re not around.

– Using Python as a bridge to enable Excel data to interact with other web applications, databases, or other external systems.

– Python scripts can be used to create custom functions not natively available in Excel, thereby expanding the scope of what can be done with Excel.

– Python can be used to periodically back up Excel files and even maintain versions (if needed).

– Python libraries like scikit-learn and statsmodels can be leveraged to apply popular machine learning, predictive analytics, and forecasting techniques, e.g. regression analysis, time series modelling, and more.

Examples

Some everyday examples of how using the power of Python in Excel could help businesses include:

– Making monthly sales reports better as well as faster and easier to produce. For example, if a sales manager needs to compile monthly sales reports and receives sales data from multiple regions in different Excel files, a Python script can be written to automatically consolidate all these files into a master report.

– Helping to track the expenses of a small business by using Python to automatically categorise and summarise expenses from an Excel sheet, thereby helping to track where money is being spent most frequently.

– In retail, a store manager could use a Python script to alert them when inventory for a particular item goes below a certain threshold (based on the data in the Excel inventory list).

– Financial analysts could predict future revenue or costs by using Python apply complex forecasting models on past financial data in Excel.

– In accounts, if a business needs to generate bulk invoices, Python can be used to save time by pulling data from an Excel sheet (like client details and amounts) and produce individual invoice files for each client.

– A business with critical data in Excel can have Python scripts scheduled to automatically back up these files at regular intervals, thereby ensuring data safety.

Other examples of what businesses can use Python scripts in combination with Excel include employee scheduling, e.g. generating shift schedules, quickly analysing any customer feedback collected in Excel, automatically highlighting best prices collected in Excel from different vendors, calculating commission for sales staff from figures collected in Excel, and analysing supplier delivery performance, e.g. delivery date and time records held in Excel.

What Does This Mean For Your Business? 

In short, releasing Python in Excel enables businesses (that leverage the integration) to effectively ‘supercharge’ their data processing and analysis capabilities, thereby giving them the ability to handle more complex tasks, larger data sets, and integrate with a broader range of technologies.

This could improve productivity, competitiveness, give new insights and reveal new business opportunities, save time, and produce better quality reports and visualisations which can improve transparency and business decision making. The fact(s) that Python in Excel doesn’t require any setup, integrates seamlessly with Teams, plus works securely in the cloud must surely also be attractive to businesses, many of whom now have remote and flexible working (all Teams users have access and security worries are minimised). Most businesses must, however, wait a little longer to start using the power of Python in Excel because it’s currently only available to users running Beta Channel on Windows and Microsoft 365 Insider Program members, although it will start to roll out with build 16.0.16818.20000, and then to the other platforms at a later date.

With last-minute holidays on people’s minds (as well as current delays and disruption) Google has announced a new money-saving feature for Google Flights which shows users the cheapest time to book.

What Is Google Flights? 

Google Flights, introduced back in 2011, is Google’s online flight booking search service which allows users to search for airline fares, book flights, and compare different flight and ticketing options. The service works by aggregating data from multiple airlines, booking agencies, and other online flight services and redirects customers to the airline’s website or a third-party booking site to complete the purchase.

New Feature 

Google says the new feature offers users an upgraded insight to help answer the question “Is it better to book now or wait for lower prices to come along?” As a supplement to Google Travel’s existing price tracking alerts and price guarantee option, the new feature can show users when prices have typically been lowest to book their chosen dates and destination (for searches with reliable trend data).

For example, the new insights feature can tell users that the cheapest time to book similar trips is usually two months before departure, and if they’re currently in that “sweet spot.” Also, for example, the new feature could show users that prices for a particular destination usually drop closer to take-off, which means users can see that that they could benefit by waiting before booking.

In short, the insights offered by the new feature could help Google Travel users save money and can make a decision with a greater sense of confidence, based on information they didn’t have before. This could also save users time in shopping around and hassle in deliberating.

Adds To The Other Money-Saving Features 

The new money saving insights supplement the existing ones on Google Travel, including:

– The ‘Price Tracking’ feature, introduced in 2017, which enables users to set up tracking for flights on specific dates so they can be automatically notified if flight prices drop significantly. Also, users can set price tracking for “Any dates” to receive emails about deals anytime in the next three to six months.

– The ‘Price Guarantee’ badge feature, introduced in April this year, and part of a US pilot, which marks some flight results with a price guarantee badge, indicating that Google Travel is “especially confident” that the price shown won’t get any lower before departure. When users book a flight marked with the guarantee badge, Google Travel monitors the price every day before take-off, and if the price does go down, users are paid the difference via Google Pay.

What Does This Mean For Your Business? 

Flight prices in the UK have increased a massive18 per cent (Kayak) from last year, partly due to rising oil prices, rising fuel import prices due to the war in Ukraine, rising maintenance costs and more, making it much more difficult to find cheap flights. Coupled with a cost of living crisis, this has made it more important than ever for consumers to shop around. However, people now have access to more price comparison services to help. For example, Google Travel has many flight comparison competitors in the UK, arguably better known than Google’s service, such as Expedia, TravelSupermarket, Opodo, Lastminute.com, Booking.com, Sky Scanner, Kayak, Cheapflights, and more. The existing price-related features and new price insight feature for Google Travel are, therefore, both likely to be helpful to consumers and companies offering lower flights as well as helping Google to compete in a busy market where Google has many strong competitors in different countries.

Insights like these are a way to add value and tie-in with the Google Travel’s existing advantages, e.g. a clean/easy interface, integration with its other services (the globally popular Google Maps app), speed, no booking fees and reliability, and give Google a leg-up. Google also has the advantage of having access to a lot of data about what travel customers are searching for and trends, and being major player in the AI world, so these new features (and likely more to come), can draw upon Google’s existing assets and strengths to keep Google Travel competitive.