Bon, il est bientôt l'heure de la pause et vous avez bien mérité de faire travailler vos méninges sur autre chose que des lignes de code ou des tableurs Excel. Ça tombe bien, je viens de tomber sur un petit jeu web qui va vous rappeler des souvenirs... Vous vous souvenez de "Des Chiffres et des Lettres" ? Cette émission où Bertrand Renard alignait des calculs pendant que vous, gamin, vous demandiez pourquoi vos parents regardaient un truc aussi barbant ?

Hé bien Make 67 s'en inspire clairement, mais en version web décontractée et sans le stress du chrono qui défile à la télé.

On vous donne 4 nombres au hasard et vous devez combiner le tout avec les opérations de base (addition, soustraction, multiplication, division) pour obtenir... 67. Pourquoi 67 ? Aucune idée, mais c'est le charme du truc. Chaque nombre ne peut être utilisé qu'une seule fois, et petit détail qui a son importance, les calculs s'effectuent de gauche à droite, pas selon l'ordre mathématique classique. Du coup 2 + 3 × 4 ça donne 20, pas 14. Faut s'y faire, mais ça rajoute une petite couche de réflexion.

L'interface est minimaliste au possible avec 4 boutons pour les nombres, 4 pour les opérations, et hop vous construisez votre expression. Et si vous vous plantez, y'a un bouton Clear pour recommencer. Mais attention, vous ne pouvez l'utiliser que 3 fois max, après quoi le bouton Solve se débloque pour vous montrer la solution. Pas de jugement, on a tous des jours sans ^^.

Le petit plus sympa c'est quand vous trouvez la bonne combinaison. Votre téléphone peut vibrer (si compatible), des confettis apparaissent et y'a même un petit son de victoire. C'est con mais ça fait plaisir. Et pour les maniaques du détail, sachez que le jeu gère proprement les divisions en arrondissant à 6 décimales.

Perso je trouve ça parfait pour une pause de 5 minutes entre deux réunions ou pour décompresser en fin de journée.

Bref, si vous cherchez un truc pour occuper votre pause café, c'est cadeau .

Pour moi, 2024 a été l'année noire de nos données personnelles en France. Et 2025 n'a pas corrigé le tir, bien au contraire. L'année qui s'est écoulée a juste confirmé qu'on était entrés dans une espèce de routine du "demain ce sera pire". Y'a pas eu un secteur épargné, pas un organisme qui n'a pas été touché. Santé, télécom, grande distribution, services publics, fédérations sportives... C'est un festival du piratage qui s'est abattu sur l'Hexagone ces 2 dernières années.

Et SaxX, le hacker éthique que vous connaissez surement, vient de publier sur son LinkedIn un bilan édifiant : 48 organisations françaises piratées en un an. La liste fait froid dans le dos.

En réalité c'est même plus que ça, puisque ça a commencé dès février 2024 avec le piratage massif de Viamedis et Almerys, les deux opérateurs de tiers payant qui gèrent la quasi-totalité des remboursements santé en France. Plus de 33 millions de Français concernés, avec leurs noms, numéros de sécu, dates de naissance... Pas les données bancaires certes, mais suffisamment pour monter des arnaques à l'usurpation d'identité bien ficelées.

Un mois plus tard, en mars 2024, c'est France Travail qui tombait. L'ex-Pôle Emploi s'est fait siphonner les données de potentiellement 43 millions de personnes inscrites au cours des 20 dernières années. Le pire c'est que la direction avait été alertée sur des faiblesses de sécu avant l'attaque. Des suspects ont été arrêtés... et c'était des gamins. Des gamins qui ont quand même eu accès aux données de la moitié du pays.

Septembre 2024 a aussi été un carnage. Un seul pirate, sous le pseudo Horror404x, a réussi à compromettre Boulanger (jusqu'à 27 millions de "lignes" revendiquées), Cultura (entre 1,5 et 2,6 millions de comptes selon les sources), Truffaut (270 000 comptes), Grosbill, Cybertek, et même l'Assurance Retraite (des centaines de milliers de retraités). Comment ? Simplement en ciblant un prestataire commun lié aux systèmes de livraison. Un seul maillon faible, et c'est toute la chaîne qui cède.

Puis en octobre-novembre 2024, ce sont les opérateurs télécoms qui se sont fait dépouiller. Free d'abord, avec plus de 19 millions de clients touchés, dont plusieurs millions avec des IBAN dans la nature. Et là, on est dans le bingo complet avec identité + coordonnées + infos contractuelles + IBAN = terrain parfait pour les arnaques "faux conseiller", les prélèvements frauduleux, les ouvertures de comptes. Ces derniers risquent d'ailleurs une amende pouvant aller jusqu'à 48 millions d'euros . Puis SFR a suivi avec au moins deux épisodes : une première fuite autour de 50 000 clients à l'automne 2024, puis des millions revendiqués ensuite. N'oubliez pas, quand ça nie, quand ça minimise, quand ça traîne... ça laisse juste plus de temps aux escrocs.

Et autour de ces gros blocs, y'a eu surtout une pluie d'incidents plus petits : Auchan, Picard, Molotov, LDLC, Norauto, Meilleurtaux... Sans oublier Direct Assurance, Speedy, Point S. Bref, 2024, c'est l'année où on a compris que ça touchait TOUT LE MONDE.

Et puis 2025 arrive, et là, le grand délire. Le piratage de nos données n'est plus une exception... Ce n'est plus un accident... C'est une industrie.

Début 2025, on voit apparaitre à nouveau des attaques "système"... C'est à dire des fournisseurs, des prestataires, des outils utilisés partout qui se font poutrer. L'exemple parfait c'est Harvest (logiciels financiers) et, par ricochet, des clients de MAIF et BPCE. Même logique que ce qu'on a eu en 2024... On tape un intermédiaire, et ça permet de toucher une grappe entière dans un secteur donné. Puis sans surprise, au printemps 2025, ça tombe comme des mouches : Intersport, Autosur, Cerballiance, Indigo, Afflelou, Carrefour Mobile, Easy Cash, Hertz... Et derrière chaque nom, c'est toujours la même chanson : "pas de données bancaires" (ok), mais tout le reste suffit largement pour faire de la merde.

L'été 2025, on a eu droit à des cibles plus "haut niveau" : Sorbonne Université, CNFPT, des acteurs santé, et côté marques : Dior, Louis Vuitton, Cartier... Côté transport y'a eu Air France et côté télécom, Bouygues Telecom ! On n'est plus sur un site e-commerce qui s'est fait péter via un formulaire php mal sécurisé...non, on est sur du volume, des identifiants, des IBAN, des chaînes d'approvisionnement complètes...

Ensuite, à l'automne 2025, c'est la sphère "sport" et "administrations" qui se fonbt hacher menu : des fédérations en cascade (souvent via des outils mutualisés), France Travail qui ressort encore, la Fédération Française de Tir (via un prestataire), et des histoires d'ARS qui donnent des sueurs froides.

Et la fin 2025, c'est la cerise radioactive sur le gâteau puisqu'on a Pajemploi, HelloWork, Leroy Merlin, Mondial Relay, Colis Privé, Eurofiber, Weda, Resana, Médecin Direct, Cuisinella, La Poste (attaque qui met à l'arrêt des services au pire moment, je pense que vous en avez tous entendu parler), le Ministère de l'Intérieur, le Ministère des Sports, PornHub...

On termine donc l'année en beauté avec l'impression que tout le monde est une cible "normale". 9 personnes sur 10 en France ont été touchées d'après SaxX. C'est dingue quand même.

Et ce qui me fait bouillir de rage, c'est qu'on est coincés, putain.

Réfléchissez deux secondes... Vous cherchez un emploi ? Vous êtes OBLIGÉS de vous inscrire à France Travail et de leur filer votre vie entière. Vous voulez être remboursé de vos frais de santé ? Pas le choix, c'est Viamedis ou Almerys. Vous voulez un téléphone ? Free, SFR, Orange... Et votre numéro de sécu, votre IBAN, votre adresse. Vous voulez une retraite (loool) ? La CNAV veut tout savoir. Et si vous refusez de donner ces infos ? Vous êtes tout simplement hors-la-loi. Pas d'emploi, pas de remboursement santé, pas de téléphone, pas de retraite. Fin de partie.

Donc le deal c'est soit vous filez vos données personnelles à des organismes qui se feront pirater tôt ou tard, soit vous vivez en ermite dans une grotte en dehors de la société. Super choix 👍.

Et qu'est-ce qu'on a en échange de cette "confiance" forcée ?

On a des systèmes d'information qui ressemblent à des passoires, des prestataires sous-payés qui deviennent des portes d'entrée open bar pour les hackers, et des communications de crise qui arrivent des semaines après les faits. "Vos données bancaires ne sont pas concernées" nous rabache-t-on à chaque fois, comme si c'était une consolation alors que notre identité COMPLÈTE est en vente pour le prix d'un Happy Meal.

Et ce qui m'inquiète le plus, c'est l'effet cumulatif car chaque fuite isolée peut sembler "gérable" mais quand vous croisez les bases de Viamedis (numéro de sécu), France Travail (historique pro), un opérateur télécom (IBAN), un distributeur (habitudes de conso)... Vous obtenez un profil complet exploitable. Y'a 600 millions de comptes qui sont partis dans la nature rien que cette année... Donc de quoi monter des arnaques ultra-ciblées, des usurpations d'identité sophistiquées, voire du chantage.

Et dans certains cas, ça va encore plus loin... Regardez le piratage de la Fédération Française de Tir avec le gars qui s'est fait attaquer chez lui ...Et c'est pas le seul... Ça montre jusqte à quel point une fuite peut devenir un risque "hors écran". Quand on sais qui est licencié, où il habite, comment le joindre... on peut mettre en place très facilement du repérages, des pressions, du ciblage. Et là, j'vous parle de risque physique, pas juste de spam ou de démarchage au téléphone. Et ça sera la même violence avec leur future loi pour collecter toutes les datas des propriétaires de wallet crypto self-custody.

Bref, je sens ce malaise qui monte de plus en plus car on nous demande toujours plus d'infos. Pour ouvrir un compte, pour s'inscrire quelque part, pour accéder à un service... et vous comme moi, savons pertinemment que ces infos vont fuiter un jour. C'est pas "si", c'est "quand", perso, j'en ai ma claque... ça commence à bien faire.

Alors voilà ma vraie question, celle que nos chers élus devraient se poser : A-t-on vraiment besoin de collecter autant de données ?

Pourquoi France Travail a besoin de garder mes infos pendant 20 ans ? Pourquoi mon opérateur télécom doit connaître mon adresse postale exacte ? Pourquoi ma carte de fidélité Auchan doit être liée à mon identité complète ? Est-ce qu'on pourrait pas, je sais pas moi, minimiser un peu tout ça ?

Et surtout, est-ce qu'on pourrait pas trouver un système qui nous permettrait de prouver notre identité sans avoir à déballer notre vie entière ? Genre juste vérifier que oui, je suis majeur, que oui, j'habite en France, sans pour autant filer mon adresse, mon numéro de téléphone, ma photo, ma carte d'identité et la liste de tous mes comptes en banque. Ces technologies existent et y'a déjà des solutions de type zero-knowledge proof. Ça fait des années que je vous en parle, mais apparemment, c'est plus simple de continuer à empiler des bases de données géantes qui finiront toutes par être piratées.

On a une CNIL qui fait ce qu'elle peut avec les moyens du bord. On a une ANSSI qui alerte et recommande. Mais où est la vraie réflexion ? Où sont les députés et les ministres qui se posent la question de la minimisation des données ? Où est le débat sur les alternatives à ce système de merde où le citoyen est obligé de tout donner pour exister socialement ?

Parce que là, on nous demande de "rester vigilants face au phishing" (lol), de "vérifier nos comptes", de "changer nos mots de passe régulièrement"... Bref, de gérer les conséquences de leurs négligences. C'est un peu comme demander aux passagers du Titanic de vider l'eau avec des seaux pendant que le capitaine continue à foncer droit sur l'iceberg suivant.

Voilà, pour moi ce bilan 2024-2025, c'est pas juste une liste de chiffres. C'est le symptôme d'une société qui a numérisé jusqu'à l’écœurement nos vies en marche forcée sans jamais se poser les bonnes questions. On a foncé tête baissée dans la collecte massive de données "parce que c'est pratique, tkt", sans jamais se demander si on en avait vraiment besoin, et sans jamais investir sérieusement pour les protéger.

Alors à nos chers décideurs, j'ai envie de dire réveillez-vous bande de moules !! Car le prochain gros piratage, c'est pas dans 10 ans, hein, c'est dans les prochains mois. Et ce sera encore 30 ou 40 millions de Français qui verront leurs données dans la nature. Ça vous semble normal ? Moi non, et je mettrais ma main à couper que je suis pas le seul à en avoir ras-le-bol.

Merci à SaxX pour ce travail de compilation et d'alerte !

Vous aussi vous avez un dossier « Notes » qui ressemble à un cimetière d'idées ? Des fichiers texte avec des noms genre « truc_important.txt » ou « a_voir_plus_tard.md » que vous n'avez jamais revus depuis 2019 ? Hé bien j'ai ce qu'il vous faut pour enfin donner un sens à tout ce bordel !

Blinko c'est une app de prise de notes qui utilise l'IA pour vous aider à retrouver ce que vous avez noté, même quand vous avez complètement oublié les mots exacts que vous aviez utilisés. Le principe c'est du RAG (Retrieval-Augmented Generation), c'est-à-dire que l'IA va fouiller dans toutes vos notes et vous ressortir les infos pertinentes quand vous posez une question. Genre « c'était quoi ce truc que j'avais noté sur les serveurs NAS ? » et hop, l'IA vous retrouve tout.

curl -o install.sh https://raw.githubusercontent.com/blinko-space/blinko/main/install.sh && bash install.sh

Vous utilisez Word pour bosser et j'imagine que vous avez vu passer le fameux Copilot de Microsoft à 30 balles par mois pour les pros ? Ouais, ça pique un peu le porte-monnaie surtout quand on a déjà nos propres clés API OpenAI ou Gemini qui traînent et sur lesquelles on claque un smic tous les mois.

Hé bien Word GPT Plus c'est justement un add-in open source qui intègre l'IA directement dans Microsoft Word, et qui vous permet d'utiliser vos propres clés API au lieu de payer un énième abonnement. Avec ça, vous pouvez générer du texte, traduire, résumer, reformuler... le tout sans quitter votre document.

Mais le truc vraiment cool, c'est le mode Agent. Là, l'IA a accès à plein d'outils qui lui permettent de manipuler directement votre document Word. Genre insérer du texte, formater des paragraphes, créer des tableaux, gérer les signets, faire des rechercher-remplacer... Vous lui dites « formate tous les titres de section en Heading 2 » et hop, c'est fait. C'est pas juste un chatbot dans une sidebar, c'est carrément un assistant qui peut agir sur votre document.

Côté fournisseurs IA, vous avez le choix entre OpenAI (GPT-4, GPT-3.5, et même les modèles compatibles comme DeepSeek), Azure OpenAI si vous êtes en entreprise, Google Gemini, Groq pour les modèles Llama et Qwen, et même Ollama si vous voulez faire tourner vos LLM en local sans envoyer vos données quelque part. Et ça, c'est top pour ceux qui bossent sur des documents confidentiels.

Y'a aussi des Quick Actions bien pratiques genre traduction en plus de 40 langues, amélioration de texte, réécriture académique, résumé automatique, correction grammaticale... Bref, les classiques mais directement accessibles dans Word.

Pour l'installer, c'est hyper simple. Vous téléchargez le fichier manifest.xml depuis le repo GitHub, vous le mettez dans un dossier partagé sur votre machine, et vous l'ajoutez dans Word via Insertion > Mes compléments > Dossier partagé. Pas besoin de coder quoi que ce soit. Y'a aussi une option Docker pour ceux qui veulent l'héberger eux-mêmes ou le déployer sur un serveur.

Niveau vie privée, vos clés API et vos prompts perso sont stockés localement dans le navigateur intégré à l'add-in Word. Y'a pas de serveur intermédiaire qui récupère vos données, sauf si vous configurez vous-même un proxy. Vos documents restent ainsi bien au chaud chez vous.

Par contre, faut Word 2016 minimum, Word 2019, 2021 ou Microsoft 365 sur Windows. Et ça marche uniquement avec les fichiers .docx.

Bref, si vous voulez avoir ChatGPT ou Gemini directement dans Word sans vous ruiner avec un abonnement Copilot, c'est exactement ce qu'il vous faut. Et comme c'est open source sous licence MIT, vous pouvez auditer le code si vous êtes du genre méfiant.

Source

Whether you’re running a business project, carrying out scientific research, or doing a spot of DIY around the house, knowing when something is “good enough” can be a tough question to answer. To me, “good enough” means something that is fit for purpose. It’s about striking a balance between the effort required to achieve perfection and the cost of not moving forward. It’s an essential mindset when perfection is either not needed or – as is often the case – not attainable.

When striving for good enough, the important thing to focus on is that your outcome should meet expectations, but not massively exceed them. Sounds simple, but how often have we heard people say things like they’re “polishing coal”, striving for “gold plated” or “trying to make a silk purse out of a sow’s ear”. It basically means they haven’t understood, defined or even accepted the requirements of the end goal.

Trouble is, as we go through school, college and university, we’re brought up to believe that we should strive for the best in whatever we study. Those with the highest grades, we’re told, will probably get the best opportunities and career openings. Unfortunately, this approach means we think we need to aim for perfection in everything in life, which is not always a good thing.

How to be good enough

So why is aiming for “good enough” a good thing to do? First, there’s the notion of “diminishing returns”. It takes a disproportionate amount of effort to achieve the final, small improvements that most people won’t even notice. Put simply, time can be wasted on unnecessary refinements, as embodied by the 80/20 rule (see box).

Good enough also helps us to focus efforts. When a consumer or customer doesn’t know exactly what they want, or a product development route is uncertain, it can be better to deliver things in small chunks. Providing something basic but usable can be used to solicit feedback to help clarify requirements or make improvements or additions that can be incorporated into the next chunk. This is broadly along the lines of a “minimum viable product”.

Not seeking perfection reminds us too that solutions to problems are often uncertain. If it’s not clear how, or even if, something might work, a proof of concept (PoC) can instead be a good way to try something out. Progress can be made by solving a specific technical challenge, whether via a basic experiment, demonstration or short piece of research. A PoC should help avoid committing significant time and resource to something that will never work.

Aiming for “good enough” naturally leads us to the notion of “continuous improvement”. It’s a personal favourite of mine because it allows for things to be improved incrementally as we learn or get feedback, rather than producing something in one go and then forgetting about it. It helps keep things current and relevant and encourages a culture of constantly looking for a better way to do things.

Finally, when searching for good enough, don’t forget the idea of ballpark estimates. Making approximations sounds too simple to be effective, but sometimes a rough estimate is really all you need. If an approximate guess can inform and guide your next steps or determine whether further action will be necessary then go for it. 

The benefits of good enough

Being good enough doesn’t just lead to practical outcomes, it can benefit our personal well-being too. Our time, after all, is a precious commodity and we can’t magically increase this resource. The pursuit of perfection can lead to stagnation, and ultimately burnout, whereas achieving good enough allows us to move on in a timely fashion.

A good-enough approach will even make you less stressed. By getting things done sooner and achieving more, you’ll feel freer and happier about your work even if it means accepting imperfection. Mistakes and errors are inevitable in life, so don’t be afraid to make them; use them as learning opportunities, rather than seeing them as something bad. Remember – the person who never made a mistake never got out of bed.

Recognizing that you’ve done the best you can for now is also crucial for starting new projects and making progress. By accepting good enough you can build momentum, get more things done, and consistently take actions toward achieving your goals.

Finally, good enough is also about shared ownership. By inviting someone else to look at what you’ve done, you can significantly speed up the process. In my own career I’ve often found myself agonising over some obscure detail or feeling something is missing, only to have my quandary solved almost instantly simply by getting someone else involved – making me wish I’d asked them sooner.

Caveats and conclusions

Good enough comes with some caveats. Regulatory or legislative requirements means there will always be projects that have to reach a minimum standard, which will be your top priority. The precise nature of good enough will also depend on whether you’re making stuff (be it cars or computers) or dealing with intangible commodities such as software or services.

So what’s the conclusion? Well, in the interests of my own time, I’ve decided to apply the 80/20 rule and leave it to you to draw your own conclusion. As far as I’m concerned, I think this article has been good enough, but I’m sure you’ll let me know if it hasn’t. Consider it as a minimally viable product that I can update in a future column.

The post When is good enough ‘good enough’? appeared first on Physics World.

As we enter the final stretch of the International Year of Quantum Science and Technology (IYQ), I hope you’ve enjoyed our extensive quantum coverage over the last 12 months. We’ve tackled the history of the subject, explored some of the unexplained mysteries that still make quantum physics so exciting, and examined many of the commercial applications of quantum technology. You can find most of our coverage collected into two free-to-read digital Quantum Briefings, available here and here on the Physics World website.

Over the last 100 years since Werner Heisenberg first developed quantum mechanics on the island of Helgoland in June 1925, quantum mechanics has proved to be an incredibly powerful, successful and logically consistent theory. Our understanding of the subatomic world is no longer the “lamentable hodgepodge of hypotheses, principles, theorems and computational recipes”, as the Israeli physicist and philosopher Max Jammer memorably once described it.

In fact, quantum mechanics has not just transformed our understanding of the natural world; it has immense practical ramifications too, with so-called “quantum 1.0” technologies – lasers, semiconductors and electronics – underpinning our modern world. But as was clear from the UK National Quantum Technologies Showcase in London last week, organized by Innovate UK, the “quantum 2.0” revolution is now in full swing.

The day-long event, which is now in its 10th year, featured over 100 exhibitors, including many companies that are already using fundamental quantum concepts such as entanglement and superposition to support the burgeoning fields of quantum computing, quantum sensing and quantum communication. The show was attended by more than 3000 delegates, some of whom almost had to be ushered out of the door at closing time, so keen were they to keep talking.

Last week also saw a two-day conference at the historic Royal Institution (RI) in central London that was a centrepiece of IYQ in the UK and Ireland. Entitled Quantum Science and Technology: the First 100 Years; Our Quantum Future and attended by over 300 people, it was organized by the History of Physics and the Business Innovation and Growth groups of the Institute of Physics (IOP), which publishes Physics World.

The first day, focusing on the foundations of quantum mechanics, ended with a panel discussion – chaired by my colleague Tushna Commissariat and Daisy Shearer from the UK’s National Quantum Computing Centre – with physicists Fay Dowker (Imperial College), Jim Al-Khalili  (University of Surrey) and Peter Knight. They talked about whether the quantum wavefunction provides a complete description of physical reality, prompting much discussion with the audience. As Al-Khalili wryly noted, if entanglement has emerged as the fundamental feature of quantum reality, then “decoherence is her annoying and ever-present little brother”.

Knight, meanwhile, who is a powerful figure in quantum-policy circles, went as far as to say that the limit of decoherence – and indeed the boundary between the classical and quantum worlds – is not a fixed and yet-to-be revealed point. Instead, he mused, it will be determined by how much money and ingenuity and time physicists have at their disposal.

On the second day of the IOP conference at the RI, I chaired a discussion that brought together four future leaders of the subject: Mehul Malik (Heriot-Watt University) and Sarah Malik (University College London) along with industry insiders Nicole Gillett (Riverlane) and Muhammad Hamza Waseem (Quantinuum).

As well as outlining the technical challenges in their fields, the speakers all stressed the importance of developing a “skills pipeline” so that the quantum sector has enough talented people to meet its needs. Also vital will be the need to communicate the mysteries and potential of quantum technology – not just to the public but to industrialists, government officials and venture capitalists. By many measures, the UK is at the forefront of quantum tech – and it is a lead it should not let slip.

The week ended with Al-Khalili giving a public lecture, also at the Royal Institution, entitled “A new quantum world: ‘spooky’ physics to tech revolution”. It formed part of the RI’s famous Friday night “discourses”, which this year celebrate their 200th anniversary. Al-Khalili, who also presents A Life Scientific on BBC Radio 4, is now the only person ever to have given three RI discourses.

After the lecture, which was sold out, he took part in a panel discussion with Knight and Elizabeth Cunningham, a former vice-president for membership at the IOP. Al-Khalili was later presented with a special bottle of “Glentanglement” whisky made by Glasgow-based Fraunhofer UK for the Scottish Quantum Technology cluster.

The post The future of quantum physics and technology debated at the Royal Institution appeared first on Physics World.

“Global collaborations for European economic resilience” is the theme of  SEMICON Europa 2025. The event is coming to Munich, Germany on 18–21 November and it will attract 25,000 semiconductor professionals who will enjoy presentations from over 200 speakers.

The TechARENA portion of the event will cover a wide range of technology-related issues including new materials, future computing paradigms and the development of hi-tech skills in the European workface. There will also be an Executive Forum, which will feature leaders in industry and government and will cover topics including silicon geopolitics and the use of artificial intelligence in semiconductor manufacturing.

SEMICON Europa will be held at the Messe München, where it will feature a huge exhibition with over 500 exhibitors from around the world. The exhibition is spread out over three halls and here are some of the companies and product innovations to look out for on the show floor.

Accelerating the future of electro-photonic integration with SmarAct

As the boundaries between electronic and photonic technologies continue to blur, the semiconductor industry faces a growing challenge: how to test and align increasingly complex electro-photonic chip architectures efficiently, precisely, and at scale. At SEMICON Europa 2025, SmarAct will address this challenge head-on with its latest innovation – Fast Scan Align. This is a high-speed and high-precision alignment solution that redefines the limits of testing and packaging for integrated photonics.

In the emerging era of heterogeneous integration, electronic and photonic components must be aligned and interconnected with sub-micrometre accuracy. Traditional positioning systems often struggle to deliver both speed and precision, especially when dealing with the delicate coupling between optical and electrical domains. SmarAct’s Fast Scan Align solution bridges this gap by combining modular motion platforms, real-time feedback control, and advanced metrology into one integrated system.

At its core, Fast Scan Align leverages SmarAct’s electromagnetic and piezo-driven positioning stages, which are capable of nanometre-resolution motion in multiple degrees of freedom. Fast Scan Align’s modular architecture allows users to configure systems tailored to their application – from wafer-level testing to fibre-to-chip alignment with active optical coupling. Integrated sensors and intelligent algorithms enable scanning and alignment routines that drastically reduce setup time while improving repeatability and process stability.

Fast Scan Align’s compact modules allow various measurement techniques to be integrated with unprecedented possibilities. This has become decisive for the increasing level of integration of complex electro-photonic chips.

Apart from the topics of wafer-level testing and packaging, wafer positioning with extreme precision is as crucial as never before for the highly integrated chips of the future. SmarAct’s PICOSCALE interferometer addresses the challenge of extreme position by delivering picometer-level displacement measurements directly at the point of interest.

When combined with SmarAct’s precision wafer stages, the PICOSCALE interferometer ensures highly accurate motion tracking and closed-loop control during dynamic alignment processes. This synergy between motion and metrology gives users unprecedented insight into the mechanical and optical behaviour of their devices – which is a critical advantage for high-yield testing of photonic and optoelectronic wafers.

Visitors to SEMICON Europa will also experience how all of SmarAct’s products – from motion and metrology components to modular systems and up to turn-key solutions – integrate seamlessly, offering intuitive operation, full automation capability, and compatibility with laboratory and production environments alike.

For more information visit SmarAct at booth B1.860 or explore more of SmarAct’s solutions in the semiconductor and photonics industry.

Optimized pressure monitoring: Efficient workflows with Thyracont’s VD800 digital compact vacuum meters

Thyracont Vacuum Instruments will be showcasing its precision vacuum metrology systems in exhibition hall C1. Made in Germany, the company’s broad portfolio combines diverse measurement technologies – including piezo, Pirani, capacitive, cold cathode, and hot cathode – to deliver reliable results across a pressure range from 2000 to 3e-11 mbar.

Front-and-centre at SEMICON Europa will be Thyracont’s new series of VD800 compact vacuum meters. These instruments provide precise, on-site pressure monitoring in industrial and research environments. Featuring a direct pressure display and real-time pressure graphs, the VD800 series is ideal for service and maintenance tasks, laboratory applications, and test setups.

The VD800 series combines high accuracy with a highly intuitive user interface. This delivers real-time measurement values; pressure diagrams; and minimum and maximum pressure – all at a glance. The VD800’s 4+1 membrane keypad ensures quick access to all functions. USB-C and optional Bluetooth LE connectivity deliver seamless data readout and export. The VD800’s large internal data logger can store over 10 million measured values with their RTC data, with each measurement series saved as a separate file.

Data sampling rates can be set from 20 ms to 60 s to achieve dynamic pressure tracking or long-term measurements. Leak rates can be measured directly by monitoring the rise in pressure in the vacuum system. Intelligent energy management gives the meters extended battery life and longer operation times. Battery charging is done conveniently via USB-C.

The vacuum meters are available in several different sensor configurations, making them adaptable to a wide range of different uses. Model VD810 integrates a piezo ceramic sensor for making gas-type-independent measurements for rough vacuum applications. This sensor is insensitive to contamination, making it suitable for rough industrial environments. The VD810 measures absolute pressure from 2000 to 1 mbar and relative pressure from −1060 to +1200 mbar.

Model VD850 integrates a piezo/Pirani combination sensor, which delivers high resolution and accuracy in the rough and fine vacuum ranges. Optimized temperature compensation ensures stable measurements in the absolute pressure range from 1200 to 5e-5 mbar and in the relative pressure range from −1060 to +340 mbar.

The model VD800 is a standalone meter designed for use with Thyracont’s USB-C vacuum transducers, which are available in two models. The VSRUSB USB-C transducer is a piezo/Pirani combination sensor that measures absolute pressure in the 2000 to 5.0e-5 mbar range. The other is the VSCUSB USB-C transducer, which measures absolute pressures from 2000 down to 1 mbar and has a relative pressure range from -1060 to +1200 mbar. A USB-C cable connects the transducer to the VD800 for quick and easy data retrieval. The USB-C transducers are ideal for hard-to-reach areas of vacuum systems. The transducers can be activated while a process is running, enabling continuous monitoring and improved service diagnostics.

With its blend of precision, flexibility, and ease of use, the Thyracont VD800 series defines the next generation of compact vacuum meters. The devices’ intuitive interface, extensive data capabilities, and modern connectivity make them an indispensable tool for laboratories, service engineers, and industrial operators alike.

To experience the future of vacuum metrology in Munich, visit Thyracont at SEMICON Europa hall C1, booth 752. There you will discover how the VD800 series can optimize your pressure monitoring workflows.

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To coincide with a week of quantum-related activities organized by the Institute of Physics (IOP) in the UK, Physics World has just published a free-to-read digital magazine to bring you up to date about all the latest developments in the quantum world.

The 62-page Physics World Quantum Briefing 2.0 celebrates the International Year of Quantum Science and Technology (IYQ) and also looks ahead to a quantum-enhanced future.

Marking 100 years since the advent of quantum mechanics, IYQ aims to raise awareness of the impact of quantum physics and its myriad future applications, with a global diary of quantum-themed public talks, scientific conferences, industry events and more.

The 2025 Physics World Quantum Briefing 2.0, which follows on from the first edition published in May, contains yet more quantum topics for you to explore and is once again divided into “history”, “mystery” and “industry”.

You can find out more about the contributions of Indian physicist Satyendra Nath Bose to quantum science; explore weird phenomena such as causal order and quantum superposition; and discover the latest applications of quantum computing.

A century after quantum mechanics was first formulated, many physicists are still undecided on some of the most basic foundational questions. There’s no agreement on which interpretation of quantum mechanics holds strong; whether the wavefunction is merely a mathematical tool or a true representation of reality; or what impact an observer has on a quantum state.

Some of the biggest unanswered questions in physics – such as finding the quantum/classical boundary or reconciling gravity and quantum mechanics – lie at the heart of these conundrums. So as we look to the future of quantum – from its fundamentals to its technological applications – let us hope that some answers to these puzzles will become apparent as we crack the quantum code to our universe.

• Read the free Physics World Quantum Briefing 2.0 today.

The post Intrigued by quantum? Explore the 2025 <em>Physics World Quantum Briefing 2.0</em> appeared first on Physics World.

Unless you’ve been living under a stone, you can’t have failed to notice that 2025 marks the first 100 years of quantum mechanics. A massive milestone, to say the least, about which much has been written in Physics World and elsewhere in what is the International Year of Quantum Science and Technology (IYQ). However, I’d like to focus on a specific piece of quantum technology, namely quantum computing.

I keep hearing about quantum computers, so people must be using them to do cool things, and surely they will soon be as commonplace as classical computers. But as a physicist-turned-engineer working in the aerospace sector, I struggle to get a clear picture of where things are really at. If I ask friends and colleagues when they expect to see quantum computers routinely used in everyday life, I get answers ranging from “in the next two years” to “maybe in my lifetime” or even “never”.

Before we go any further, it’s worth reminding ourselves that quantum computing relies on several key quantum properties, including superposition, which gives rise to the quantum bit, or qubit. The basic building block of a quantum computer – the qubit – exists as a combination of 0 and 1 states at the same time and is represented by a probabilistic wave function. Classical computers, in contrast, use binary digital bits that are either 0 or 1.

Also vital for quantum computers is the notion of entanglement, which is when two or more qubits are co-ordinated, allowing them to share their quantum information. In a highly correlated system, a quantum computer can explore many paths simultaneously. This “massive scale” parallel processing is how quantum may solve certain problems exponentially faster than a classical computer.

The other key phenomenon for quantum computers is quantum interference. The wave-like nature of qubits means that when different probability amplitudes are in phase, they combine constructively to increase the likelihood of the right solution. Conversely, destructive interference occurs when amplitudes are out of phase, making it less likely to get the wrong answer.

Quantum interference is important in quantum computing because it allows quantum algorithms to amplify the probability of correct answers and suppress incorrect ones, making calculations much faster. Along with superposition and entanglement, it means that quantum computers could process and store vast numbers of probabilities at once, outstripping even the best classical supercomputers.

Towards real devices

To me, it all sounds exciting, but what have quantum computers ever done for us so far? It’s clear that quantum computers are not ready to be deployed in the real world. Significant technological challenges need to be overcome before they become fully realisable. In any case, no-one is expecting quantum computers to displace classical computers “like for like”: they’ll both be used for different things.

Yet it seems that the very essence of quantum computing is also its Achilles heel. Superposition, entanglement and interference – the quantum properties that will make it so powerful – are also incredibly difficult to create and maintain. Qubits are also extremely sensitive to their surroundings. They easily lose their quantum state due to interactions with the environment, whether via stray particles, electromagnetic fields, or thermal fluctuations. Known as decoherence, it makes quantum computers prone to error.

That’s why quantum computers need specialized – and often cryogenically controlled – environments to maintain the quantum states necessary for accurate computation. Building a quantum system with lots of interconnected qubits is therefore a major, expensive engineering challenge, with complex hardware and extreme operating conditions. Developing “fault-tolerant” quantum hardware and robust error-correction techniques will be essential if we want reliable quantum computation.

As for the development of software and algorithms for quantum systems, there’s a long way to go, with a lack of mature tools and frameworks. Quantum algorithms require fundamentally different programming paradigms to those used for classical computers. Put simply, that’s why building reliable, real-world deployable quantum computers remains a grand challenge.

What does the future hold?

Despite the huge amount of work that still lies in store, quantum computers have already demonstrated some amazing potential. The US firm D-Wave, for example, claimed earlier this year to have carried out simulations of quantum magnetic phase transitions that wouldn’t be possible with the most powerful classical devices. If true, this was the first time a quantum computer had achieved “quantum advantage” for a practical physics problem (whether the problem was worth solving is another question).

There is also a lot of research and development going on around the world into solving the qubit stability problem. At some stage, there will likely be a breakthrough design for robust and reliable quantum computer architecture. There is probably a lot of technical advancement happening right now behind closed doors.

The first real-world applications of quantum computers will be akin to the giant classical supercomputers of the past. If you were around in the 1980s, you’ll remember Cray supercomputers: huge, inaccessible beasts owned by large corporations, government agencies and academic institutions to enable vast amounts of calculations to be performed (provided you had the money).

And, if I believe what I read, quantum computers will not replace classical computers, at least not initially, but work alongside them, as each has its own relative strengths. Quantum computers will be suited for specific and highly demanding computational tasks, such as drug discovery, materials science, financial modelling, complex optimization problems and increasingly large artificial intelligence and machine-learning models.

These are all things beyond the limits of classical computer resource. Classical computers will remain relevant for everyday tasks like web browsing, word processing and managing databases, and they will be essential for handling the data preparation, visualization and error correction required by quantum systems.

And there is one final point to mention, which is cyber security. Quantum computing poses a major threat to existing encryption methods, with potential to undermine widely used public-key cryptography. There are concerns that hackers nowadays are storing their stolen data in anticipation of future quantum decryption.

Having looked into the topic, I can now see why the timeline for quantum computing is so fuzzy and why I got so many different answers when I asked people when the technology would be mainstream. Quite simply, I still can’t predict how or when the tech stack will pan out. But as IYQ draws to a close, the future for quantum computers is bright.

• More information about the quantum marketplace can be found in the 2025 Physics World Quantum Briefing 2.0 and in a two-part article by Philip Ball (available here and here).

The post Quantum computing: hype or hope? appeared first on Physics World.

When it comes to building a fully functional “fault-tolerant” quantum computer, companies and government labs all over the world are rushing to be the first over the finish line. But a truly useful universal quantum computer capable of running complex algorithms would have to entangle millions of coherent qubits, which are extremely fragile. Because of environmental factors such as temperature, interference from other electronic systems in hardware, and even errors in measurement, today’s devices would fail under an avalanche of errors long before reaching that point.

So the problem of error correction is a key issue for the future of the market. It arises because errors in qubits can’t be corrected simply by keeping multiple copies, as they are in classical computers: quantum rules forbid the copying of qubit states while they are still entangled with others, and are thus unknown. To run quantum circuits with millions of gates, we therefore need new tricks to enable quantum error correction (QEC).

Protected states

The general principle of QEC is to spread the information over many qubits so that an error in any one of them doesn’t matter too much. “The essential idea of quantum error correction is that if we want to protect a quantum system from damage then we should encode it in a very highly entangled state,” says John Preskill, director of the Institute for Quantum Information and Matter at the California Institute of Technology in Pasadena.

There is no unique way of achieving that spreading, however. Different error-correcting codes can depend on the connectivity between qubits – whether, say, they are coupled only to their nearest neighbours or to all the others in the device – which tends to be determined by the physical platform being used. However error correction is done, it must be done fast. “The mechanisms for error correction need to be running at a speed that is commensurate with that of the gate operations,” says Michael Cuthbert, founding director of the UK’s National Quantum Computing Centre (NQCC). “There’s no point in doing a gate operation in a nanosecond if it then takes 100 microseconds to do the error correction for the next gate operation.”

At the moment, dealing with errors is largely about compensation rather than correction: patching up the problems of errors in retrospect, for example by using algorithms that can throw out some results that are likely to be unreliable (an approach called “post-selection”). It’s also a matter of making better qubits that are less error-prone in the first place.

1 From many to few

Qubits are so fragile that their quantum state is very susceptible to the local environment, and can easily be lost through the process of decoherence. Current quantum computers therefore have very high error rates – roughly one error in every few hundred operations. For quantum computers to be truly useful, this error rate will have to be reduced to the scale of one in a million; especially as larger more complex algorithms would require one in a billion or even trillion error rates. This requires real-time quantum error correction (QEC).

To protect the information stored in qubits, a multitude of unreliable physical qubits have to be combined in such a way that if one qubit fails and causes an error, the others can help protect the system. Essentially, by combining many physical qubits (shown above on the left), one can build a few “logical” qubits that are strongly resistant to noise.

According to Maria Maragkou, commercial vice-president of quantum error-correction company Riverlane, the goal of full QEC has ramifications for the design of the machines all the way from hardware to workflow planning. “The shift to support error correction has a profound effect on the way quantum processors themselves are built, the way we control and operate them, through a robust software stack on top of which the applications can be run,” she explains. The “stack” includes everything from programming languages to user interfaces and servers.

With genuinely fault-tolerant qubits, errors can be kept under control and prevented from proliferating during a computation. Such qubits might be made in principle by combining many physical qubits into a single “logical qubit” in which errors can be corrected (see figure 1). In practice, though, this creates a large overhead: huge numbers of physical qubits might be needed to make just a few fault-tolerant logical qubits. The question is then whether errors in all those physical qubits can be checked faster than they accumulate (see figure 2).

That overhead has been steadily reduced over the past several years, and at the end of last year researchers at Google announced that their 105-qubit Willow quantum chip passed the break-even threshold at which the error rate gets smaller, rather than larger, as more physical qubits are used to make a logical qubit. This means that in principle such arrays could be scaled up without errors accumulating.

2 Error correction in action

The illustration gives an overview of quantum error correction (QEC) in action within a quantum processing unit. UK-based company Riverlane is building its Deltaflow QEC stack that will correct millions of data errors in real time, allowing a quantum computer to go beyond the reach of any classical supercomputer.

Fault-tolerant quantum computing is the ultimate goal, says Jay Gambetta, director of IBM research at the company’s centre in Yorktown Heights, New York. He believes that to perform truly transformative quantum calculations, the system must go beyond demonstrating a few logical qubits – instead, you need arrays of at least a 100 of them, that can perform more than 100 million quantum operations (10⁸ QuOps). “The number of operations is the most important thing,” he says.

It sounds like a tall order, but Gambetta is confident that IBM will achieve these figures by 2029. By building on what has been achieved so far with error correction and mitigation, he feels “more confident than I ever did before that we can achieve a fault-tolerant computer.” Jerry Chow, previous manager of the Experimental Quantum Computing group at IBM, shares that optimism. “We have a real blueprint for how we can build [such a machine] by 2029,” he says (see figure 3).

Others suspect the breakthrough threshold may be a little lower: Steve Brierley, chief executive of Riverlane, believes that the first error-corrected quantum computer, with around 10 000 physical qubits supporting 100 logical qubits and capable of a million QuOps (a megaQuOp), could come as soon as 2027. Following on, gigaQuOp machines (10⁹ QuOps) should be available by 2030–32, and teraQuOps (10¹² QuOp) by 2035–37.

Platform independent

Error mitigation and error correction are just two of the challenges for developers of quantum software. Fundamentally, to develop a truly quantum algorithm involves taking full advantage of the key quantum-mechanical properties such as superposition and entanglement. Often, the best way to do that depends on the hardware used to run the algorithm. But ultimately the goal will be to make software that is not platform-dependent and so doesn’t require the user to think about the physics involved.

“At the moment, a lot of the platforms require you to come right down into the quantum physics, which is a necessity to maximize performance,” says Richard Murray of photonic quantum-computing company Orca. Try to generalize an algorithm by abstracting away from the physics and you’ll usually lower the efficiency with which it runs. “But no user wants to talk about quantum physics when they’re trying to do machine learning or something,” Murray adds. He believes that ultimately it will be possible for quantum software developers to hide those details from users – but Brierley thinks this will require fault-tolerant machines.

“In due time everything below the logical circuit will be a black box to the app developers”, adds Maragkou over at Riverlane. “They will not need to know what kind of error correction is used, what type of qubits are used, and so on.” She stresses that creating truly efficient and useful machines depends on developing the requisite skills. “We need to scale up the workforce to develop better qubits, better error-correction codes and decoders, write the software that can elevate those machines and solve meaningful problems in a way that they can be adopted.” Such skills won’t come only from quantum physicists, she adds: “I would dare say it’s mostly not!”

Yet even now, working on quantum software doesn’t demand a deep expertise in quantum theory. “You can be someone working in quantum computing and solving problems without having a traditional physics training and knowing about the energy levels of the hydrogen atom and so on,” says Ashley Montanaro, who co-founded the quantum software company Phasecraft.

On the other hand, insights can flow in the other direction too: working on quantum algorithms can lead to new physics. “Quantum computing and quantum information are really pushing the boundaries of what we think of as quantum mechanics today,” says Montanaro, adding that QEC “has produced amazing physics breakthroughs.”

Early adopters?

Once we have true error correction, Cuthbert at the UK’s NQCC expects to see “a flow of high-value commercial uses” for quantum computers. What might those be?

In this arena of quantum chemistry and materials science, genuine quantum advantage – calculating something that is impossible using classical methods alone – is more or less here already, says Chow. Crucially, however, quantum methods needn’t be used for the entire simulation but can be added to classical ones to give them a boost for particular parts of the problem.

For example, last year researchers at IBM teamed up with scientists at several RIKEN institutes in Japan to calculate the minimum energy state for the iron sulphide cluster (4Fe-4S) at the heart of the bacterial nitrogenase enzyme that fixes nitrogen. This cluster is too big and complex to be accurately simulated using the classical approximations of quantum chemistry. The researchers used a combination of both quantum computing (with IBM’s 72-qubit Heron chip) and RIKEN’s Fugaku high performance computing (HPC). This idea of “improving classical methods by injecting quantum as a subroutine” is likely to be a more general strategy, says Gambetta. “The future of computing is going to be heterogeneous accelerators [of discovery] that include quantum.”

Likewise, Montanaro says that Phasecraft is developing “quantum-enhanced algorithms”, where a quantum computer is used, not to solve the whole problem, but just to help a classical computer in some way. “There are only certain problems where we know quantum computing is going to be useful,” he says. “I think we are going to see quantum computers working in tandem with classical computers in a hybrid approach. I don’t think we’ll ever see workloads that are entirely run using a quantum computer.” Among the first important problems that quantum machines will solve, according to Montanaro, are the simulation of new materials – to develop, for example, clean-energy technologies (see figure 4).

“For a physicist like me,” says Preskill, “what is really exciting about quantum computing is that we have good reason to believe that a quantum computer would be able to efficiently simulate any process that occurs in nature.”

3 Structural insights

A promising application of quantum computers is simulating novel materials. Researchers from the quantum algorithms firm Phasecraft, for example, have already shown how a quantum computer could help simulate complex materials such as the polycrystalline compound LK-99, which was purported by some researchers in 2024 to be a room-temperature superconductor.

Using a classical/quantum hybrid workflow, together with the firm’s proprietary material simulation approach to encode and compile materials on quantum hardware, Phasecraft researchers were able to establish a classical model of the LK99 structure that allowed them to extract an approximate representation of the electrons within the material. The illustration above shows the green and blue electronic structure around red and grey atoms in LK-99.

Montanaro believes another likely near-term goal for useful quantum computing is solving optimization problems – both here and in quantum simulation, “we think genuine value can be delivered already in this NISQ era with hundreds of qubits.” (NISQ, a term coined by Preskill, refers to noisy intermediate-scale quantum computing, with relatively small numbers of rather noisy, error-prone qubits.)

One further potential benefit of quantum computing is that it tends to require less energy than classical high-performance computing, which is notoriously high. If the energy cost could be cut by even a few percent, it would be worth using quantum resources for that reason alone. “Quantum has real potential for an energy advantage,” says Chow. One study in 2020 showed that a particular quantum-mechanical calculation carried out on a HPC used many orders of magnitude more energy than when it was simulated on a quantum circuit. Such comparisons are not easy, however, in the absence of an agreed and well-defined metric for energy consumption.

Building the market

Right now, the quantum computing market is in a curious superposition of states itself – it has ample proof of principle, but today’s devices are still some way from being able to perform a computation relevant to a practical problem that could not be done with classical computers. Yet to get to that point, the field needs plenty of investment.

The fact that quantum computers, especially if used with HPC, are already unique scientific tools should establish their value in the immediate term, says Gambetta. “I think this is going to accelerate, and will keep the funding going.” It is why IBM is focusing on utility-scale systems of around 100 qubits or so and more than a thousand gate operations, he says, rather than simply trying to build ever bigger devices.

Montanaro sees a role for governments to boost the growth of the industry “where it’s not the right fit for the private sector”. One role of government is simply as a customer. For example, Phasecraft is working with the UK national grid to develop a quantum algorithm for optimizing the energy network. “Longer-term support for academic research is absolutely critical,” Montanaro adds. “It would be a mistake to think that everything is done in terms of the underpinning science, and governments should continue to support blue-skies research.”

It’s not clear, though, whether there will be a big demand for quantum machines that every user will own and run. Before 2010, “there was an expectation that banks and government departments would all want their own machine – the market would look a bit like HPC,” Cuthbert says. But that demand depends in part on what commercial machines end up being like. “If it’s going to need a premises the size of a football field, with a power station next to it, that becomes the kind of infrastructure that you only want to build nationally.” Even for smaller machines, users are likely to try them first on the cloud before committing to installing one in-house.

According to Cuthbert , the real challenge in the supply-chain development is that many of today’s technologies were developed for the science community – where, say, achieving millikelvin cooling or using high-power lasers is routine. “How do you go from a specialist scientific clientele to something that starts to look like a washing machine factory, where you can make them to a certain level of performance,” while also being much cheaper, and easier to use?

But Cuthbert is optimistic about bridging this gap to get to commercially useful machines, encouraged in part by looking back at the classical computing industry of the 1970s. “The architects of those systems could not imagine what we would use our computation resources for today. So I don’t think we should be too discouraged that you can grow an industry when we don’t know what it’ll do in five years’ time.”

Montanaro too sees analogies with those early days of classical computing. “If you think what the computer industry looked like in the 1940s, it’s very different from even 20 years later. But there are some parallels. There are companies that are filling each of the different niches we saw previously, there are some that are specializing in quantum hardware development, there are some that are just doing software.” Cuthbert thinks that the quantum industry is likely to follow a similar pathway, “but more quickly and leading to greater market consolidation more rapidly.”

However, while the classical computing industry was revolutionized by the advent of personal computing in the 1970s and 80s, it seems very unlikely that we will have any need for quantum laptops. Rather, we might increasingly see apps and services appear that use cloud-based quantum resources for particular operations, merging so seamlessly with classical computing that we don’t even notice.

That, perhaps, would be the ultimate sign of success: that quantum computing becomes invisible, no big deal but just a part of how our answers are delivered.

• In the first instalment of this two-part article, Philip Ball explores the latest developments in the quantum-computing industry

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