Technology

A milestone in quantum physics — rooted in a student project What began as a student's undergraduate thesis at Caltech — later continued as a graduate student at MIT — has grown into a collaborative experiment between researchers from MIT, Caltech, Harvard, Fermilab, and Google Quantum AI. Using Google’s Sycamore quantum processor, the team simulated traversable wormhole dynamics — a quantum system that behaves analogously to how certain wormholes are predicted to work in theoretical physics. Here’s what they did: Implemented two coupled SYK-like quantum systems on the processor that represent black holes in a holographic model. Sent a quantum state into one system. Applied an effective “negative energy” pulse to make the simulated wormhole traversable. Observed the state emerge on the other side — consistent with quantum teleportation. This wasn’t just classical computer modeling — it ran on real qubits, using 164 two-qubit quantum gates across nine qubits. Why it matters: The results are consistent with the ER=EPR conjecture, which suggests a deep link between quantum entanglement and spacetime geometry. In the holographic picture, patterns of entanglement can be interpreted as wormhole-like “bridges.” This experiment shows how quantum processors can begin to probe aspects of quantum gravity in a laboratory setting, complementing astrophysical observations and theoretical work. While no physical wormhole was created, this is a step toward using quantum computers to explore some of the most fundamental questions in physics. What breakthrough in science excites you most? Share your thoughts below — and let’s discuss how quantum computing is reshaping our understanding of reality. ♻️ Repost to help people in your network. And follow me for more posts like this. CC: thebrighterside

McKinsey & Company 𝗮𝗻𝗮𝗹𝘆𝘇𝗲𝗱 𝟭𝟱𝟬+ 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗚𝗲𝗻𝗔𝗜 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁𝘀 — 𝗮𝗻𝗱 𝗳𝗼𝘂𝗻𝗱 𝗼𝗻𝗲 𝗰𝗼𝗺𝗺𝗼𝗻 𝘁𝗵𝗿𝗲𝗮𝗱: ⬇️ One-off solutions don’t scale. The most successful projects take a different path: They use open, modular architectures that enable speed, reuse, and control. → Designed for reuse → Able to plug in best-in-class capabilities → Free from vendor lock-in This is the reference architecture McKinsey now recommends — optimized to scale what works while staying compliant. It consists of five core components: ⬇️ 𝟭. 𝗦𝗲𝗹𝗳-𝘀𝗲𝗿𝘃𝗶𝗰𝗲 𝗽𝗼𝗿𝘁𝗮𝗹: → A secure, compliant “pane of glass” where teams can launch, monitor, and manage GenAI apps. → Preapproved patterns, validated capabilities, shared libraries. → Observability and cost controls built-in. 𝟮. 𝗢𝗽𝗲𝗻 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 → Services are modular, reusable, and provider-agnostic. → Core functions like RAG, chunking, or prompt routing are shared across apps. → Infra and policy as code, built to evolve fast. 𝟯. 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗴𝘂𝗮𝗿𝗱𝗿𝗮𝗶𝗹𝘀 → Every prompt and response is logged, audited, and cost-attributed. → Hallucination detection, PII filters, bias audits — enforced by default. → LLMs accessed only through a centralized AI gateway. 4. 𝗙𝘂𝗹𝗹-𝘀𝘁𝗮𝗰𝗸 𝗼𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆 → Centralized logging, analytics, and monitoring across all solutions → Built-in lifecycle governance, FinOps, and Responsible AI enforcement → Secure onboarding of use cases and private data controls → Enables policy adherence across infrastructure, models, and apps 5. 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗴𝗿𝗮𝗱𝗲 𝗨𝘀𝗲 𝗖𝗮𝘀𝗲𝘀 → Modular setup for user interface, business logic, and orchestration → Integrated agents, prompt engineering, and model APIs → Guardrails, feedback systems, and observability built into the solution → Delivered through the AI Gateway for consistent compliance and scale The message is clear: If your GenAI program is stuck, don’t look at the LLM. Look at your platform. 𝗜 𝗲𝘅𝗽𝗹𝗼𝗿𝗲 𝘁𝗵𝗲𝘀𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁𝘀 — 𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝘁𝗵𝗲𝘆 𝗺𝗲𝗮𝗻 𝗳𝗼𝗿 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝘂𝘀𝗲 𝗰𝗮𝘀𝗲𝘀 — 𝗶𝗻 𝗺𝘆 𝘄𝗲𝗲𝗸𝗹𝘆 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿. 𝗬𝗼𝘂 𝗰𝗮𝗻 𝘀𝘂𝗯𝘀𝗰𝗿𝗶𝗯𝗲 𝗵𝗲𝗿𝗲 𝗳𝗼𝗿 𝗳𝗿𝗲𝗲: https://lnkd.in/dbf74Y9E

🔋 What’s really powering the AI boom? We love talking about GPUs and data, but AI’s biggest bottleneck might be electricity. As the global AI footprint surges, the question is no longer just about compute — 👉 Where will the power come from to feed this intelligence? Let’s look at the current landscape: 🌍 Global Energy Mix (2024, IEA Data): 🛢️ Oil: ~29% of global energy use ⚡ Electricity from oil: Still powers backup systems & off-grid compute in many countries ⚛️ Nuclear: ~10% of electricity worldwide — but provides >20% in the US, ~70% in France ☀️ Solar & wind: Now ~12% of global electricity, but growing fast (solar up 26% YoY) 🔋 AI power demand: Projected to double by 2026 (IEA), with AI data centers consuming up to 4% of global electricity by 2030 Meanwhile, hyperscalers are racing ahead: Amazon aims to run 100% on renewables by 2025 Microsoft just signed a deal with Helion for nuclear fusion Google is investing in AI-optimized green energy grids But the big picture remains complex: ⚠️ Oil prices still influence logistics and backup energy 🟢 Nuclear offers baseload stability, but rollout is slow ☀️ Solar/wind are promising but need smarter grids + storage Here’s the real discussion: 💬 Can AI go fully green? Or will oil and nuclear remain essential allies for scale? 💬 Should governments treat data center energy like strategic infrastructure — on par with water or transport? Would love to hear views from those in: AI infrastructure Energy policy Cloud/data center operations Clean tech and sustainability Let’s talk: 🧠 How should we power the future of intelligence? #AI #Energy #Oil #Nuclear #Renewables #DataCenters #Sustainability #CleanTech #Infrastructure #ESG #DigitalTransformation via @globejunkk #innovation #Technology

The Data (Use and Access) Act (DUAA) brings changes to the UK's rules on cookies and similar technologies. This briefing explains the three new consent exceptions, the new penalty regime, and whether you still need a cookie banner. — The DUAA amends the Privacy and Electronic Communications Regulations 2003 (PECR). Among other things, PECR regulates cookies, pixels, and other methods of accessing or storing information on people's devices. I'm using "cookies" as a shorthand (sorry). The basic PECR rule remains the same. Before setting cookies (etc), you must: • Tell people about your purposes, and • Get consent. There have always been two exceptions. You don’t need consent if the cookies (etc) are: • Used solely to facilitate the transmission of a communication, or • Strictly necessary for providing a service requested by the user. These “classic” PECR exceptions remain, with some clarifying language. — The DUAA adds three new consent exceptions. New exception 1: "Analytics" You won't need consent to collect statistical information about how your own service or website is used, with the specific aim of making improvements to it. You may not share information collected with another party except for the purpose of helping you make improvements. New exception 2: "Appearance" You won't need consent to adapt how your website appears or functions based on users' preferences, or to enhance functionality on the user’s device (e.g., for "responsive design"). — Note: You can only rely on exceptions 1 or 2 if: • You provide clear and comprehensive information to the user about your specific purposes, • You give the user a simple and free way to object (opt out), and • The user has not objected. — New exception 3: "Emergencies" You do not need consent to access or store information on a person's device if: • You get a communication from the device requesting emergency assistance, and • You access or store information on the person’s device to discover where it is, with a view to providing emergency assistance. This exception doesn’t require you to allow objections or provide information. — Do you still need a cookie banner for the UK? While you will be able to set certain cookies by default (on an “opt-out”) basis, you probably still need some sort of cookie banner or pop-up, even if your cookies fall within one of the new exceptions. I give a hypothetical example of an opt-out cookie banner in the briefing. But hold off for now: We still need to wait for the Government to give effect to the DUAA. — The DUAA also aligns PECR’s enforcement regime with the UK GDPR. In other words… Maximum fines under PECR are rising from £500,000 to £17.5 million. Recent UK regulatory activity in this area has primarily consisted of sending people letters. So there is no guarantee that a large cookie-related fine will ever be issued in the UK… But you should be aware of the possibility.

The waste from solar panels is dwarfed by the waste from fossil fuels and other streams. A popular myth circulates every now and again claiming the rapid global uptake of solar generation will lead to mountains of waste. Is that really the case? ➡️ A 20 kg solar panel can easily generate 10 MWh over its lifetime. That's 2 kg of solid waste per MWh generated. ➡️ Coal, on the other hand, generates a whopping ~90 kg of fly ash and bottom ash per MWh. Not to mention the ~950 kg of CO2 per MWh. ➡️ And what about gas? Sure, there's no solid waste like there is with coal, but there is around 450 kg of CO2 per MWh, not to mention the upstream methane leakage. There's no comparison. Then factor in that most solar panel waste - glass, aluminium, silicon - is highly recyclable and inert. Solar panel recycling infrastructure can scale to handle future volumes. The same cannot be said of coal ash, which is a heady mix of arsenic, mercury and other toxins. We do not have a way to remove this from contaminated groundwater. We also cannot suck CO2 out of the atmosphere fast enough to make a meaningful difference. Let's be clear: the myth about mountains of waste from solar panels is fossil fuel industry propaganda. What is damaging the environment is the more than 100 billion tonnes of CO2 dumped into the atmosphere over 5 years from combustion of coal and gas. The issue isn't waste from end of life solar panels, the issue is fossil fuel waste. Let's focus on what really matters. #energy #sustainability #renewables #energytransition

Last week, I heard from a super impressive customer who has cracked the code on how to give salespeople something they’ve always wanted: more selling time. Here’s how he transformed their process. This customer runs the full B2B sales motion at an awesome printing business based in the U.S. For years, his team divided their time across six key areas: 1. Task prioritization 2. Meeting prep 3. Customer responses 4. Prospecting 5. Closing deals 6. Sales strategy Like every sales leader I know, he wants his team to spend most of their time on #5 and #6 — closing deals and sales strategy. But together, those only made up about 30% of their week. (Hearing this gave me flashbacks to my time in sales…and all that admin tasks 😱) Now, his team uses AI across the sales process to compress the amount of time spent on #1-4: 1. Task prioritization → AI scores leads and organizes daily tasks 2. Meeting prep → AI surfaces insights from calls and contact records before meetings 3. Customer responses → Breeze Customer Agent instantly answers customer questions 4. Prospecting → Breeze Prospecting Agent automatically researches accounts and books meetings The result? Higher quantity of AI-powered work: More prospecting. More pipeline.  Higher quality of human-led work: More thoughtful conversations. Sharper strategy. This COO's story made my week. It's a reminder of just how big a shift we're going through – and why it’s such an exciting time to be in go-to-market right now.

I think a very visible observation at this year's Restaurant Show was logical tech instead of theoretical. There was less "glimpses into the future" and more "proof of concept." Here's one of those in action: For two and a half years, Wingstop has worked on a new Smart Kitchen that forecasts demand in 15-minute increments, telling the store how many wings to drop. The system takes into account more than 300 variables tailored to each unit, like weather, sales trends, and sports. It also features digital touch-screen displays at every work station instead of paper chits and an order-ready screen at the front so consumers can keep up with their order. Another feature: there are now sticker print outs that identify what flavors are in each package. At restaurants where the technology has been installed, wait times have been cut in half to about 10 minutes, and there have been notable improvements in guest satisfaction, accuracy, consistency, and employee turnover. In the delivery channel, Wingstop has been able to show up in under 30 minutes. Why is this important? Shorter wait times allow the brand to become a greater consideration. Instead of serving as a destination—with an average frequency of just three times per quarter and once a month—the quicker service could entice guests to visit more often, especially during on-the-go periods like the afternoon daypart. The Wingstop Smart Kitchen is in 400 restaurants and the chain hopes to complete the rollout by the end of the year. Again, real-time innovation in the back of the house. That seems to be the battleground right now. More here: https://lnkd.in/eMHMUkmZ

The Irish Government has just announced plans to introduce the Regulation of Artificial Intelligence Bill in its Spring 2025 legislative programme, a pivotal piece of legislation aimed at giving full effect to the European Union’s Artificial Intelligence Act (EU Regulation 2024/1689). Even though the AI Act as a regulation has direct effect, this move is set to shape the national regulatory framework for AI governance in Ireland and establish national enforcement mechanisms in line with the EU’s approach. At the heart of the bill is the designation of Ireland’s National Competent Authorities: the entities that will be responsible for enforcing compliance with the AI Act. These authorities will oversee risk classification, conduct market surveillance, and impose penalties for violations. Given Ireland’s role as the EU base for major technology firms including Google, Anthropic, Meta, and TikTok, the effectiveness of its enforcement regime will be closely scrutinised across the EU and beyond. The Irish Government’s approach will be particularly significant due to the country’s track record in regulating the digital sector. Ireland’s Data Protection Commission (DPC) has wielded considerable influence over EU-wide enforcement of the GDPR, given the presence of multinational tech firms within the state. The DPC was designated as one of ireland’s nine fundamental rights authorities under the AI Act in November 2024. The bill will include provisions for penalties, though details remain unspecified. Under the EU AI Act, non-compliance can result in fines of up to €35 million or 7% of a company’s global annual turnover, whichever is higher. For Ireland, the challenge will be ensuring its enforcement framework has sufficient resources and expertise to oversee AI systems deployed within its jurisdiction. Tech industry leaders and legal experts will be closely monitoring how Ireland structures its national framework. The AI Act imposes strict obligations on high-risk AI applications, including those used in healthcare, banking, and recruitment. Companies will be required to maintain transparency, conduct impact assessments, and ensure that their AI systems do not lead to unlawful discrimination or harm. Ireland’s legislative initiative comes at a time of growing regulatory scrutiny over AI’s impact on society, innovation, and human rights. The AI Act represents the world’s most comprehensive attempt to regulate artificial intelligence, at a time other jurisdictions such as the USA are moving in the opposite regulatory direction. The Regulation of Artificial Intelligence Bill is still in its early stages, at the “Heads in Preparation” point. In the Irish legislative process, the Heads of a Bill serve as a blueprint for the eventual legislation. As Ireland moves toward full implementation of the AI Act, the government’s decisions on AI oversight will have significant implications for businesses, consumers, and the broader EU regulatory landscape.

Germans have installed 500,000 balcony solar arrays, or "balkonkraftwerk." Installations has surged thanks to simplified permitting, the ability to buy panels at hardware stores for a few hundred dollars, and renters (not just owners) being able to install the panels. Cumulatively all of the installations account for 200MW of solar. Each system is small -- capped 800 watts, but I like the spirit of individual energy independence and decisions consumers can make to combat climate change and protect their wallets from surging electricity costs. Great example of deploying climate tech for the built world that exists now and makes financial sense. Image via Solar Monkey #realestate #climate

A big question looms over generative AI: what really is its impact on the environment? I spent months investigating a single campus of Microsoft data centers in the Arizona desert - designated in part for OpenAI - in an attempt to find out. The process underscored just how little visibility we have into basic information, such as the water and energy consumption of these silicon monstrosities, which are now being built at an unprecedented rate, including in the desert. While Microsoft has invested massively to improve the sustainability of its data centers, it is also a for-profit company. At times it has suppressed environmental impact measures or pushed the opposite narrative from internal projections, even as employees urged more transparency. Meanwhile, after I FOIA'ed several agencies at the state, county, and city levels, the city returned relevant docs with all of the numbers redacted. (Screenshot attached.) Neither are willing to inform the public about the real-world costs supporting this technological wave amid an accelerating global climate crisis. My latest for The Atlantic. https://lnkd.in/guPJs8wZ