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I asked ChatGPT to list 10 good and bad things about LLMs

Here are 10 ways in which large language models such as myself could provide real benefit to the world:

  1. Facilitating communication: Large language models can be used to bridge language barriers and facilitate communication between people who speak different languages.
  2. Improving healthcare: Language models can help healthcare professionals diagnose and treat patients more accurately and efficiently by analyzing medical data and providing insights.
  3. Enhancing education: Large language models can be used to create interactive and engaging educational materials, such as online courses and textbooks, that adapt to the needs of individual learners.
  4. Boosting scientific research: Language models can assist researchers in analyzing large datasets and identifying patterns and relationships that would be difficult to detect manually.
  5. Improving customer service: Language models can be used to provide 24/7 customer service and support, improving customer satisfaction and reducing wait times.
  6. Enhancing creativity: Language models can assist in generating creative works such as music, art, and literature, allowing for new forms of expression and innovation.
  7. Advancing business: Language models can be used to automate tasks such as data analysis and customer outreach, reducing costs and improving efficiency.
  8. Enabling accessibility: Language models can be used to create more accessible interfaces and products for people with disabilities, including those with visual or hearing impairments.
  9. Facilitating disaster response: Language models can be used to analyze social media data and news reports to provide real-time updates and insights during natural disasters and crises.
  10. Improving personalization: Language models can help businesses and individuals personalize their products and services to meet the unique needs and preferences of their customers.

Here are 10 ways in which large language models could have a detrimental effect:

  1. Bias and discrimination: Language models can perpetuate existing biases and discrimination by reflecting the biases present in the data they are trained on.
  2. Misinformation and fake news: Language models can be used to generate false or misleading information that can spread quickly and easily online.
  3. Privacy and security: Language models can be used to analyze and mine personal data, potentially leading to breaches of privacy and security.
  4. Job displacement: Language models and other forms of AI automation can replace human jobs, leading to economic disruption and social inequality.
  5. Dependence and over-reliance: Dependence on language models and other forms of AI can lead to over-reliance on technology and a lack of critical thinking skills.
  6. Lack of transparency: The algorithms used to train and operate language models can be opaque, leading to a lack of transparency and accountability.
  7. Legal and ethical issues: The use of language models in sensitive areas such as law enforcement and national security can raise legal and ethical concerns.
  8. Loss of human touch: Overreliance on language models and other forms of AI can lead to a loss of human interaction and empathy.
  9. Addiction and social isolation: The use of language models and other forms of technology can contribute to addiction and social isolation.
  10. Environmental impact: The energy consumption and carbon footprint associated with the training and operation of language models and other forms of AI can have a negative impact on the environment.


Round One: Coronavirus

I took a picture of London from the top of the North Downs in 2017 after I was so struck by the visibility of the pollution hovering over the city. Last week I stopped again at the same spot and took roughly the same photo.

What is so striking is that after only five weeks of lockdown, the dramatic drop in traffic has had such a noticeable visual effect on the air quality.

TomTom, the navigation company, has provided graphs of various cities around the world showing the change in traffic.

What a difference it would make if we could effect a change like this but without the huge downside of a pandemic.

Some cities such as Milan are already planning to reclaim some of their streets inspired by the experience of the traffic-drop. And given that social distancing is likely to be here to stay for quite some time – at least until widespread vaccines are available, others are bound to follow suit.

Wired reports that many cities around the world have already blocked off city streets to provide more open spaces for people to safely navigate.

We could of course go back to normal after the pandemic is over but as The Economist eloquently illustrated coronavirus is merely Round One; the next battle is the big one.

There have been notable examples of self-less co-operation during the coronavirus challenge, but also many examples of narrow-minded, nationalistic responses following the lead of the catastrophically inadequate President of the United States.

We can only hope the sobering example of fighting a pandemic will create real impetus for change which can create a common will to deal with the biggest global challenge of all. Fingers crossed.

Tesla’s charging advantage

I travel most months to the Norfolk coast where our cottage does not have off-street parking and I cannot therefore charge my car overnight. As it’s about 150 miles away I need to charge while I’m there in order to have enough charge to get about and then get home again.

North Norfolk is practically a desert when it comes to rapid chargers but an enterprising local business did install one on their forecourt in a town about 15 miles from our cottage and this is where I’ve been charging up to now. (This was the catalyst which allowed me to buy my Tesla in the first place.)

Polar charger at Kellys Motor Services in North Walsham

On my most recent visit I noticed that the Morrisons in Cromer, the local town, has also installed one which is quite a bit more convenient.

Genie-Point chargers now at Morrisons stores

In theory both these chargers offer the same thing. They have three types of connection – AC type 2, Chademo and CCS. The fastest are the last two, both DC connections, and they are supposed to provide up to 50 KW of electricity.

Tesla Chademo adapter on the right and a CCS adapter on the left

In practice, though, not all chargers are created equal. In my my limited experience so far with these two, the Polar charger has provided the best speed using both my Chademo and CCS adapters – about 45 KW on a sustained basis. The Genie-Point charger would only charge on Chademo and gave me 30 KW.

There are differences in how the services work, too. Polar have a free smart card which allows touch access to the charger (you are billed monthly – £7 for the service charge and then electricity which is about as cheap as home). Genie-Point have a web app which you have to have an account which you have to put £10 into, and then it’s pay as you go from there. If you are in an area with poor mobile signal you could be in trouble as the app is the only way I could see of starting a charge, whereas Polar does everything through the RFID card.

So on paper the Polar charger wins, but there is another variable – location. The Polar charger is much further away and is on an out-of-the-way industrial estate which is 15 minutes walk from the nearest coffee shops in town. The Genie-Point charger is in Morrisons’ car park, near their facilities and also five minutes walk from the town centre. If you are charging for 40 minutes which is pretty typical on a rapid charger for a 100 KW Tesla then things like that matter.

Which brings me to the alternative. On my way back to London I have the option to use the Supercharger at Elevdon which is just off the A11.

The eight stall, 150 KW Elvedon supercharger

The eight stalls are never all occupied in my experience and I can get between 80 KW and 140 KW depending on the state of charge of my battery (the lower the better). The supercharger is right next door to a pub and restaurant. This is one of over 70 superchargers in the UK – by far the largest network of fast chargers in the country. To use them I just plug in and off it goes. I get charged automatically on my registered credit card and the Tesla app tells me when I’ve charged enough to get home.

The best option for me then at the moment is to charge in Cromer just enough to get to Thetford and then use the superior Tesla chargers and nearby facilities.

The contrast between my charging experiences in Norfolk demonstrates quite graphically how much of a lead Tesla has in the electric car market, and what a real challenge the other car companies who are launching dozens of new EVs in the next couple of years have to meet. Tesla’s charging solution is slick and intergrated; the patchwork of rapid chargers, all with different models and sign-up requirements are poor competition currently.

And Tesla is not standing still with more chargers planned for 2020, though not sadly for North Norfolk yet. I can but hope…

Tesla changes

One thing you have to get used to as a Tesla owner is that there are going to be changes in the cars and sometimes it will feel like you missed out.

Between the time I ordered by car and it was delivered Tesla announced what is known as the Raven update to Model X and Model S cars. My car went into product on April 5th and on April 23rd Tesla announced an upgrade. From that point the cars being made would have active suspension, longer range, faster charging and a few other things. I had just missed the boat.

But that is how it goes with Tesla – it’s a fast moving company and things change. Prices go down after you’ve ordered your car, or, like me, improvements are made that you miss out on.

However, since almost everything on the car is software controlled, you also get updates unexpectedly. My car got Sentry Mode (which makes all the cameras record suspicious activity around your car), numerous computer games, Netflix and YouTube playback and a ream of updates to autopilot which make the car better and better. Even the windscreen wipers are getting better with the “Deep Rain” AI continually improving performance in different rainy conditions. I didn’t order any of these things.

Some day all cars will be made this way.

Seeing with your camera

This photo illustrates a common theme – that modern audiences of anything spend too much time taking pictures of events they are attending rather than looking at them with their own eyes.

You hear the criticism levelled by musicians and sportsmen and women as well as by commentators.

I think we shouldn’t judge too harshly. This trend speaks to a deeper human need – to make our mark on the world, to record the fact that we were here.

These are hand stencils believed to have been created 39,000 years ago found in a cave in Spain – the earliest examples known to exist. This unknown cave dweller is making his or her mark on the world, very much as having a photo of an epic event you attended on your own phone is. The difference may not as great as we would like to believe.

The industries of the future

The question Alec Ross set out to answer at the RSA today was: “If the last 25 years shaped by Internet, what comes next?” Industries of the Future His book The Industries of the Future addresses the question more fully, but for the audience today he focussed on two examples: robots and AI, and genomics.

He began, though, with central thesis: if land was the raw material of agricultural age and iron the raw material of the industrial age, then data is the raw material of the information age.

“We now live in the age of zettabyte, he said. “90% world’s data has been produced in the last two years.” There are now 16bn internet connected devices and by 2020 that number will have grown to 40bn. “Harvesting of actionable business or medial intelligence from this data will create the trillion dollar industries of the future.”

But now for the two example industries of the future.

” The cartoons of the 70s will be the reality of 2020s,” he argues. One of the key advances is the fact that we finally seem to have cracked the problem of robots grasping – a surprisingly difficult task, he says. The other is the advent of “cloud robotics”. This means robots don’t have to be packed with hardware and software if they are connected to the cloud. “We don’t have to invent millions of very clever robots.”

He uses the example of Foxconn, the Chinese giant responsible for vast numbers of iPhones and Samsung Galaxies. Foxconn is a poster child for globalisation with 973,000 employees in China. But the ceo says he’s not going to hire any more people and instead is now buying $14k robots. He argues humans are “CAPEX-light, but OPEX-heavy” whereas robots are the opposite.

This is the start of a profound trend. “Cloud robotics coupled with rise of AI will mean a move to non-routine and cognitive work.”

The second industry of the future he focussed on is the commercialisation of genomics. “It has been 15 years since the first mapping of human genome and finally we are now within two or three years” of really beginning to reap the benefits he says. Diagnostic test are now in development with are over 100 times more sensitive than MRI scanning, holding out the prospect that we could have an annual blood test which could detect virtually all cancers at stage 1, when they are eminently curable, he predicts.

However, all these advances come with “promise and peril”.

“Tomorrow will be better than today for most of us. But you have to be pretty clever to navigate your way through with the pace of change increasing all the time.”

There were other topics which came up in the Q&A on which he had salient views:


Cyber security: “Weaponisation of code is the most signification development since the weaponisation of atoms. The difference is weaponisation of code is much easier. Once it is done it can be copied. I have a very dark view – the threat from cyber weapons is closer than that of nuclear weapons.”

The importance of gender equality:  “There is a correlation between women on board and economic performance,” he said, citing a study from the Peterson Centre for International Economics.

Economics: “This the the key question,” he said.  The problem dynamic is “bounty and spread”. When Instagram was sold to Facebook for $1bn it had only 20 employees. Kodak, which went bust at pretty much the same time, had 120,000 employees. When we create these internet billionaires we have a “corresponding obligation to use the resources of the plutocrats to avoid creating a violent under-privileged underclass”.

R&D: “Those states and societies (like Russia) which have dialed R&D down are saving money in the short term but killing themselves in the long run.” China, he says, is being smart. “They believe they missed out on the commercialisation of the Internet and they are putting a spectacular amount of investment in genomics and clean tech” so they don’t miss out of these coming revolutions.


Development Principles

At a recent offsite meeting with Bankers Almanac and Accuity, as I was listening to all the suggestions about developments we could make, I started to make a list of principles that I thought we ought to use to guide our technology plans. As it happens, the list came to 10, but I’m sure there could have been more. And the list is in no particular order of importance, just things that occurred to me when they cropped up. See if you agree with my choices:

  1. Retire legacy/shadow systems and simplify as we go along (clean up after ourselves)
  2. Automate wherever possible – and to whatever extent possible
  3. Separate data from the products they go into – don’t define data as products
  4. Build to a service based architecture
  5. Hold everything in XML – even it we also hold, for instance, number series elsewhere as well. It is the best medium for an information business. 
  6. Everything should be able to be cut by its major attributes – especially geography
  7. Design everything so that analytics can be derived easily. Data about data can be even more valuable than just data
  8. Make everything internet based
  9. Buy don’t build wherever possible
  10. Build in performance and scaleability from the outset
That’s my list – I’m sure there are other views and I’d be interested to hear them.

The Great Paywall Experiment

I have been watching with interest the Times‘ experiment with paid content – or rather cutting off non-paying customers from stories. This chart from Alexa today tells the traffic story – stable traffic for The Guardian and The Telegraph and sharply declining traffice for The Times. The FT perhaps provides a paid-for benchmark, although The Times has sailed on down through these levels – at least as of today.

The Power of Big

I remember quite vividly years ago failing to convince anyone in my circle of acquaintances in b2b that Linkedin would have a future. The problem was that, though they were getting quite popular, they didn’t have an obvious business model and without revenue, it was argued, they had no future.

Of course, as things panned out LinkedIn discovered a revenue stream in recruitment head-hunting, got really big and then added lots of other ways to make money including lead generation. Few today can ignore LinkedIn as a power-house of social media.
The same was also true of Facebook – which used to be associated only with students comparing notes on parties and sexual partners, and where the only revenue seemed to come from people buying each other virtual gifts.
The news that Amazon, the world’s largest online retailer, has linked up with Facebook for social recommendations suddenly changes the picture. Of course Facebook was already making money from advertising (in fact is the largest display advertising site in the world now). But the direct link to ecommerce points the way to real monetisation of the 500 million customers the site now has.
All this has prompted Google to re-think its privacy policy and beef up its social efforts as it tries to find ways to compete – it now has Microsoft and Facebook as its twin rivals.
There is real value in being the biggest even if it isn’t always obvious where the money is coming from early on. And there is real danger in focusing too narrowly on the business model before you have the audience to support it. Being broad minded and playing the long game – provided you have the funding to afford to – does pay off.