Before we start, I’d like to thank ESA’s Mark McCaughrean who helped kick off this article by referring me to two key articles that lay out, in scientific terms, how global warming really works.
Here you can pick your favorite temperature unit: C F (Test temperature: )
Feel free to skip this wordy intro and head straight to the model, or even to the summary at the end of this post!

I won an award! Earlier this year I was lured to the NLUUG spring conference, and after my presentation (on machine learning from scratch), the two large presentation rooms were joined for some additional announcements. Turns out this was to give me an NLUUG Lifetime Achievement Award!
Previous awardees include Piet Beertema, Guido van Rossum, Wietse Venema, Bram Moolenaar, Andy Tanenbaum, Wytze van der Raay, Teus Hagen, Michiel Leenaars, Olaf Kolkman and these are all awesome people who made massive contributions to the world and the Internet.

Tussen de enorme blogposts van 6000 woorden over het klimaat, hier wat luchtige observaties over denken, voelen en wetgeving.
Denken en voelen zijn twee wegen om tot beslissingen te komen. Beide zijn waardevol. We hoeven maar te horen van een situatie en we hebben er al gevoelens over, nog voor er veel feiten in beeld zijn.
Foto © Avery Evans via Unsplash
Een huis uitkiezen is een goed voorbeeld – je kunt verliefd worden op de tuin, of op het idee dat je je leven voortaan zo zal inrichten dat je ook tijd in die tuin gaat steken.

“Controversieelverklaard worden die wetsvoorstellen en onderwerpen waarvan redelijkerwijze verwacht mag worden dat behandeling met een ander kabinet tot een andere uitkomst zal leiden.” – website Eerste Kamer
Al bijna drie jaar is er een spoedwet in de maak om de wetgeving voor de Nederlandse Inlichtingen- en Veiligheidsdiensten ingrijpend te veranderen. Ik schreef hier eerder uitgebreid over, en ik sprak er (samen met vele anderen) ook over in een rondetafel gesprek in de Tweede Kamer (video, spreektekst met voetnoten).

This is a companion page to my blog post on global warming (which is currently not yet ready).
I put up this post already as a teaser for my upcoming global warming post, which desperately needs expert review before I dare put it online. If you are an experienced climate/atmospheric scientist, would you please consider helping me out? Please email me on bert@hubertnet.nl if you can spare the time to skim my work for gross errors.

Nothing on this page is factually controversial. However, many things in this post make for uncomfortable reading. And, climate discourse is now so politicized that many factual statements are taken as dog whistles. For example, in what follows I will state that climate has always been changing, and has in fact never been stable for very long.
This is 100% true, but people interpret this as if the writer means that our current climate change is not caused by human beings, or is nothing to worry about.

I wrote this piece after an early-career friend of mine asked some very good questions on how to be useful. Since this is a thing I struggle a bit with myself, I thought it worthwhile to write up my thoughts. Note that I fully understand that not everyone has the luxury to think about their career like this – you first have to take care of yourself and family before you can start fretting about if your working life is saving the world!

Recently, I wrote a small open source tool to make the official Dutch national address & building database more accessible. More about the tool below, but first an introduction.
Last data update: 2025-01-09
If all you need is an up to date CSV file of all Dutch addresses, their zipcodes and coordinates, scroll down to the end. If all you need is a web service, try https://berthub.eu/pcode/2513AA/14. For more details (including a live demo), do read on.

"Best een goede samenvatting eigenlijk" — een daadwerkelijke energie-expert
Op 10 juni 2023 is dit artikel uit 2022 ge-update met een extra stukje over waterstof en waar het niet voor geschikt is, plus wat meer over kernenergie, en over minder energie verbruiken.
Sinds een tijdje maak ik grafiekjes van hoe Nederland aan z’n elektriciteit komt. En soms ben ik daar dan enthousiast over, zeker als de wind waait en de zon goed schijnt.

This is a mirror of the original about:intel post, since the about:intel server is sadly sometimes overloaded. Also do read the opposing view from Jan-Jaap Oerlemans and the reflection by Lotte Houwing
The Dutch government is proposing adding a lex specialis to its existing intelligence and security services act. This addition significantly changes the scope of many powers and also extends who they can be applied to.
A draft of an English summary of this proposed law can be found here.

Gisteren (5 april) was er een technische briefing van de AIVD en MIVD over de tijdelijke wet cyberoperaties, gevolgd door een rondetafelgesprek met deskundigen. Vorige week was er een technische briefing door de toezichthouders TIB en CTIVD.
Mijn spreektekst met veel klikbare voetnoten ter verduidelijking staat hier. Er was een goeie opkomst van geïnteresseerden en Kamerleden, en er waren goede en goed geïnformeerde vragen.
Verder schreven de media over de bijeenkomsten: De Correspondent, NRC, Trouw, AD, GeenStijl

Vielen Dank an Lili Laguna für diese Übersetzung diesen niederländischen Blog-Beitrag. English version.
Jeder überschlägt sich mit Vorhersagen über KI. Sie wird uns von stupider Arbeit befreien, sie wird unsere Bildung zerstören, wir alle werden nichts mehr lernen müssen, weil die KI es für uns tun wird, Kriminelle werden uns mit ihr austricksen, Gauner werden mit ihr unendliche Mengen an Desinformation erzeugen, und die KI wird entkommen und in der realen Welt gefährlich werden.

This is a machine-aided translation of this Dutch post. Und jetzt auch auf Deutsch verfügbar!
Everyone is tumbling over themselves making predictions about AI. It’s going to free us from menial work, it’s going to dismantle our education, we all won’t have to learn things anymore because the AI will do it for us, criminals will trick us with it, crooks will create endless amounts of disinformation with language models, and the AI will escape and become dangerous in the real world.

Update: This article is now also available in English. Und jetzt auch auf Deutsch!
Iedereen buitelt over zichzelf heen om voorspellingen te doen over AI. Het gaat ons bevrijden van dom werk, het gaat ons onderwijs ontmantelen, we hoeven allemaal dingen niet meer te leren want de AI gaat het voor ons doen, criminelen zullen ons er mee bedonderen, boeven gaan er eindeloze hoeveelheden desinformatie mee maken, en de AI zal ontsnappen en in de echte wereld gevaarlijk worden.

This page is part of the Hello Deep Learning series of blog posts. You are very welcome to improve this page via GitHub!
After having completed this series of blogposts (well done!) you should have a good grounding in what deep learning is actually doing. However, this was of course only a small 20k word introduction, so there is a lot left to learn.
Unfortunately, there is a lot of nonsense online.

This page is part of the Hello Deep Learning series of blog posts. You are very welcome to improve this page via GitHub!
The previous chapters have often mentioned the chasm between “deep learning models that work on my data” and “it actually works in the real world”. It is perhaps for this reason that almost all demos and YouTube tutorials you find online never do any real world testing.

This page is part of the Hello Deep Learning series of blog posts. You are very welcome to improve this page via GitHub!
In the previous chapter we found ways to speed up our character recognition learning by a factor of 20 by using a better optimizer, and a further factor of four by cleverly using threads using a ‘shared nothing architecture’. We also learned how we can observe the development of parameters.

This page is part of the Hello Deep Learning series of blog posts. You are very welcome to improve this page via GitHub!
In the previous chapter we successfully trained a network to recognize handwritten letters, but it took an awfully long time. This is not just inconvenient: networks that take too long to train mean we can experiment less. Some things really are out of reach if each iteration takes 24 hours, instead of 15 minutes.

This page is part of the Hello Deep Learning series of blog posts. You are very welcome to improve this page via GitHub!
In the previous chapter we taught a network of linear combinations and ‘rectified linear units’ to recognize handwritten digits reasonably successfully. But we already noted that the network would be sensitive to the exact location of pixels, and that it does not in any meaningful way “know” what a 7 looks like.

This page is part of the Hello Deep Learning series of blog posts. You are very welcome to improve this page via GitHub!
In the previous chapter we described how automatic differentiation of the result of neural networks works.
In the first and second chapters we designed and trained a one-layer neural network that could distinguish images of the digit 3 and the digit 7, and the network did so very well.

This page is part of the Hello Deep Learning series of blog posts. You are very welcome to improve this page via GitHub!
In the previous chapter we configured a neural network and made it learn to distinguish between the digits 3 and 7. The learning turned out to consist of “twisting the knobs in the right direction”. Although simplistic, the results were pretty impressive. But, you might still be a bit underwhelmed - the network only distinguished between two digits.

This page is part of the Hello Deep Learning series of blog posts. You are very welcome to improve this page via GitHub!
In this chapter we’re going to take the neural network we made earlier, but actually make it do some learning itself. And, oddly enough, this demonstration will again likely simultaneously make you wonder “is this all??” and also impress you by what even this trivial stuff can do.

This page is part of the Hello Deep Learning series of blog posts. You are very welcome to improve this page via GitHub!
In this chapter we’re going to build our first neural network and take it for a spin. Weirdly, this demonstration will likely simultaneously make you wonder “is this all??” and also impress you by what even this trivial stuff can do.
The first part of this chapter covers the theory, and shows no code.

This page is part of the Hello Deep Learning series of blog posts. Also, feel free to skip this intro and head straight for chapter 1 where the machine learning begins!
Deep learning and ‘generative AI’ have now truly arrived. If this is a good thing very much remains to be seen. What is certain however is that these technologies will have a huge impact.
Up to late 2022, I had unwisely derided the advances of deep learning as overhyped nonsense from people doing fake demos.

A from scratch GPU-free introduction to modern machine learning. Many tutorials exist already of course, but this one aims to really explain what is going on, from the ground up. Also, we’ll develop the demo until it is actually useful on real life data which you can supply yourself.
Other documents start out from the (very impressive) PyTorch environment, or they attempt to math it up from first principles. Trying to understand deep learning via PyTorch is like trying to learn aerodynamics from flying an Airbus A380.

This is a living document - I’d normally spend a few days polishing everything, but since CRA talks are ongoing right now, there’s simply no time for that. Check back frequently for updates! Also please let me know urgently on bert@hubertnet.nl if you think I’m reading things incorrectly!
As a follow-up to my earlier post on the EU Cyber Resilience Act, here I’d like to address some practicalities: how would it actually work.

First a round of thanks for the many people in industry and government who provided valuable links, background and insights! I could not have done this without your help! If you spot any mistakes, or have suggestions, please do contact me on bert@hubertnet.nl
The EU’s new Cyber Resilience Act is admirable in its goal. And the EU is not alone in thinking something needs to be done about the dreadful state of security online – the Biden administration has just released its National Cybersecurity Strategy that has similar aims.

“The history of human thought would make it seem that there is difficulty in thinking of an idea even when all the facts are on the table” – Isaac Asimov
In 2014, MIT’s Technology Review wrote a very interesting article about an attempt to have Isaac Asimov be part of a group of scientists attempting to think outside of the box. In this article they included a 1959 essay that Asimov wrote instead of continuing to taking part in this (classified) government work.

Deze reactie is als PDF ook te vinden op de site internetconsultatie.nl. Ook kan er tot en met 16 januari nog gereageerd worden.
Aan de minister van Binnenlandse Zaken en Koninkrijksrelaties, H.G.J Bruins Slot
en aan minister van Defensie, K.H. Ollongren
Betreft: Tijdelijke wet onderzoeken AIVD en MIVD naar landen met een offensief cyberprogramma
Geachte ministers,
In aanvulling op de uitstekende reacties van mijn voormalige collega’s van de Toetsingscommissie Inzet Bevoegdheden, de stichting Bits of Freedom en het College voor de Rechten van de Mens wil ik graag het volgende kwijt.

Deze pagina is mede tot stand gekomen door kritisch commentaar & feedback van Marien Boonman en Hidde Brugmans & anonieme experts. Dank! En mochten er desondanks fouten zijn -> bert@hubertnet.nl
We beginnen simpel, een woonhuis zonder zonnepanelen, verbruik minder dan 10.000kWh/jaar.
Je elektriciteitsrekening bestaat (volgens de regels geldend op op 2 januari 2023) dan uit de volgende componenten:
De kale kWh-prijs die je energieleverancier verzonnen heeft (waarover later meer, per kWh) Opslag Duurzame Energie- en Klimaattransitie (ODE) (3,05 cent per kWh in 2022, 0 cent in 2023) Energiebelasting (3,679 cent per kWh, 12,599 cent per kWh in 2023) BTW over al het bovenstaande (9% laatste helft 2022, per 1 januari 2023 weer 21%) Dit samen is wat je elektriciteitsbedrijf hun “tarief per kWh inclusief belastingen” moet noemen.