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date: '2023-04-07T11:14:41.131905'
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<img src="/media/2023/04/07/1680866081_0.jpg" class="u-photo" />
Happy freaking Easter James - from Mother Nature
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date: '2023-04-21T07:05:00.448091'
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<img src="/media/2023/04/21/1682060700_0.jpg" alt= "James stood at the front of a hall in front of a projection screen with a crowd watching" class="u-photo" />
I had a great time speaking about AI risks and rewards for small and medium businesses at the Rare Earth Digital debrief in Nantwich last night. The Crown is a lovely venue too and the quirky, wattle and daub wonky architecture reminded me of my childhood home.
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<img src="/media/2023/06/03/1685811118_0.jpg" alt="Two Juicy Ripe Strawberries On A Red Chopping Board." class="u-photo" />
First strawberries of the year from the garden
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## Bot Detection ## Bot Detection
There are certainly opportunities in bot vs human detection. Solutions like GPTZero [^GPTZero] and GLTR[^GLTRGlitterV0] rely on the statistical likelihood that a model would use a given sequence of words based on historical output (for example if the words "bananas in pajamas" never appear in known GPT output but they appear in the input document, the probability that it was written by a human is increased). Approaches like DetectGPT [^mitchellDetectGPTZeroShotMachineGenerated2023] use a model to perturb (subtly change) the output and compare the probabilities of the strings being generated to see if the original "sticks out" as being unusual and thus more human-like. There are certainly opportunities in bot vs human detection. Solutions like GPTZero [^GPTZero] and GLTR[^GLTRGlitterV0] rely on the statistical likelihood that a model would use a given sequence of words based on historical output (for example if the words "bananas in pajamas" never appear in known GPT output but they appear in the input document, the probability that it was written by a human is increased). Approaches like DetectGPT [^mitchellDetectGPTZeroShotMachineGenerated2023] use a model to perturb (subtly change) the output and compare the probabilities of the strings being generated to see if the original "sticks out" as being unusual and thus more human-like. ***edit: I was also contacted by Tracey Deacker - a computer science student in Reykjavik, who recommended CrossPlag[^CrossPlag] - another such detection tool.***
It seems like bot detection and evading detection are likely to be a new arms race: as new detection methods emerge, people will build more and more complex methods for evading detection or rely on adversarial training approaches to train existing models to evade new detection approaches automatically. It seems like bot detection and evading detection are likely to be a new arms race: as new detection methods emerge, people will build more and more complex methods for evading detection or rely on adversarial training approaches to train existing models to evade new detection approaches automatically.
@ -119,3 +119,4 @@ https://link.medium.com/6Bz5jc2hsyb - a blog post from an NLP professor about fi
[^ribeiroAccuracyBehavioralTesting2020]: Ribeiro, M. T., Wu, T., Guestrin, C., & Singh, S. (2020). Beyond Accuracy: Behavioral Testing of NLP Models with CheckList. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 49024912. https://doi.org/10.18653/v1/2020.acl-main.442 [^ribeiroAccuracyBehavioralTesting2020]: Ribeiro, M. T., Wu, T., Guestrin, C., & Singh, S. (2020). Beyond Accuracy: Behavioral Testing of NLP Models with CheckList. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 49024912. https://doi.org/10.18653/v1/2020.acl-main.442
[^morrisTextAttackFrameworkAdversarial2020]: Morris, J. X., Lifland, E., Yoo, J. Y., Grigsby, J., Jin, D., & Qi, Y. (2020). TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP (arXiv:2005.05909). arXiv. https://doi.org/10.48550/arXiv.2005.05909 [^morrisTextAttackFrameworkAdversarial2020]: Morris, J. X., Lifland, E., Yoo, J. Y., Grigsby, J., Jin, D., & Qi, Y. (2020). TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP (arXiv:2005.05909). arXiv. https://doi.org/10.48550/arXiv.2005.05909
[^knightSloppyUseMachine]: Knight, W. (n.d.). Sloppy Use of Machine Learning Is Causing a Reproducibility Crisis in Science. Wired. Retrieved 25 March 2023, from https://www.wired.com/story/machine-learning-reproducibility-crisis/ [^knightSloppyUseMachine]: Knight, W. (n.d.). Sloppy Use of Machine Learning Is Causing a Reproducibility Crisis in Science. Wired. Retrieved 25 March 2023, from https://www.wired.com/story/machine-learning-reproducibility-crisis/
[^CrossPlag]: AI Content Detector - Crossplag - https://crossplag.com/ai-content-detector/

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title: "Introducing Turbopilot"
date: 2023-04-16T14:08:55Z
description: My local intelligent auto-complete project
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I started TurboPilot over the easter weekend when I was stuck at home bored with COVID. As an AI specialist, I've been following OpenAI, Copilot and all things GPT very closely and I've been enspired excited by all the open activity like [llama.cpp](https://github.com/ggerganov/llama.cpp) which allows you to run large language models locally on CPU. I decided that it might be quite useful to have intelligent code autocompletion that runs locally without sending my data to the OpenAI mothership for analysis and when I'm travelling with limited connectivity like on trains or planes.

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title: "An IRL Update"
date: 2023-05-23T21:13:45+01:00
description: a brief update - I've been AWOL for a bit.
url: /2023/5/23/an-irl-update
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You might have noticed that I've not been particularly active online as of late. Well that's for a variety of reasons. Firstly [my company raised £2.8M funding](https://www.uktech.news/ai/filament-funding-20230509) and, since then, I've been working hard hiring, documenting and trying to rework a number of processes so that they will still work once the company gets much bigger.
Earlier in May Mrs R and I went on holiday to the Lake District to celebrate my birthday. The Lake District is one of my favourite places in the UK and I have personal connections to a number of places up there, it was great to get away from screens for a few days and spend some time in the great outdoors.
{{<figure src="images/lakedistrict.jpg" caption="The view from our hotel room in The Belsfield Hotel on the shore of Lake Windermere">}}
While I was on holiday, I also started reading [Stolen Focus by Johann Hari](https://bookwyrm.social/book/322172/s/stolen-focus) which discusses a number of modern phenomena which are sapping our collective abilities to pay attention, focus and be creative and making us anxious (being anxious makes it hard to focus too...). Being online, reading clickbait, doomscrolling, reading and responding to reactionary stuff on social media, these are all thing that are pretty bad for our attention spans so I've resolved to try and reduce the time I'm spending doing these activities, spend more time away from computers in general and try to be more deliberate about the time I do spend online. I wouldn't say I'm doing a digital detox but more of a digital de-clutter. I've been seeing [similar updates](https://kevquirk.com/anti-social-update) from people in my online circles too.
I've not paid [turbopilot](https://github.com/ravenscroftj/turbopilot) as much attention as I'd have liked recently as there are only so many hours in the day. However, I will put out some updates and write about my plans there very soon.s

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