Thomas Hawk posted a photo:

Thomas Hawk posted a photo:

Slanted Magazine #48?Seoul offers a vivid insight into South Korea's contemporary creative scene, exploring everything from graphic design, typography, and visual communication to architecture, product design, and digital media.

Jonathan Bailey, Ella Purnell, Aimee-Lou Wood, Maggie Gyllenhaal and more bring shock and gore to an immersive retelling with real bite

Do we really need another retelling of Bram Stoker’s fabled horror novel, which has already yielded multiple films, plays and radio dramas? Perhaps not, but this new audio version of Dracula, directed by Mary Lambert and adapted by Robyn Aherne, justifies its existence with an unusually star-studded cast, a streamlined story and an immersive and frequently nightmarish sound palette.

Bridgerton’s Jonathan Bailey is smooth and charismatic as the eponymous count who invites a young solicitor, Jonathan Harker (Louis Partridge), to his castle in Transylvania to assist him with the sale of a property. There, Harker becomes increasingly uneasy as he glimpses the count’s diabolical powers and realises that he is, in fact, a prisoner.

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Using AI for roles from executive assistants to chiefs of staff, companies are boasting about doing more with less, creating tension with their human workers

On an average workday, Dhruv Amin chats with dozens of colleagues to get things done at his AI startup Anything. He might ask Gwen, his executive assistant, to schedule a meeting, then troubleshoot a technical problem with Cody, his coding partner. Then he might check in with Betsy for search engine optimization, or Juno for onboarding customers. If the office runs out of snacks, he sends a Slack message to Justin, the office manager charged with stocking the kitchen.

But none of these co-workers are people. They’re artificial intelligence agents, software that handles tasks without human intervention. Anything is one of several startups building them, and betting on a future where workplaces will increasingly turn over their sales, marketing, coding and other tasks to semi-autonomous AI. At Anything, there are 15 human employees and roughly 150 agents – a ratio that Amin believes will soon be the norm.

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Michael Stonebraker introduced Postgres® at Berkeley in 1986. Forty years later, the database he invented is a leading choice for a generation of AI projects, and he is among the sharpest skeptics of how those projects are being built. Bruce Momjian is cofounder and core team member of the PostgreSQL Global Development Group, and he works at EnterpriseDB (EDB). In upcoming episodes of AI & Data Horizons by EnterpriseDB (EDB), the Turing Award winner and MIT professor and the Postgres community advocate both make the case that the future belongs to systems that bend without breaking, and to communities that no single company controls. Zero, not 80 Stonebraker’s first exhibit is text-to-SQL, the promise that a business user can ask a question in plain English and get an answer from the warehouse. Public benchmarks such as Spider and BIRD report accuracy above 80 percent. His team tried the same thing on MIT’s own data warehouse—1,400 tables of student, faculty, building, and salary information—using real queries from its SQL log. “We got zero-percent accuracy. Not 80, not 70, not 40—zero,” he said. Adding agentic AI, retrieval, and prompt engineering lifted that level into the teens. Telling the model every table and join term reached the 30s. “Still not ready for prime time.” The reasons are the stuff of every enterprise estate. There is no training data, because the warehouse is not on the public internet. The data is idiosyncratic: among other things, MIT buildings have numbers, not names. The schema has rotted into cryptic table and column names and overlapping views. And real queries are harder than benchmark ones. His team has published its own benchmark, Beaver, and says nobody has broken out of accuracy levels in the 30-percent range. Use the model for what it’s good at The deeper problem, Stonebraker argues, is architectural. Large language models are good with text, but “what they are no good at is doing joins of structured data,” which is most of what an enterprise holds. Working with the city of Munich’s transport department, Stonebraker’s team found that answering a single citizen complaint about crosswalk timing meant combining regulations, CAD drawings, trolley schedules, and school-zone maps. Orchestrating that with a language model at the center was, he said, “ridiculously expensive.” The team’s answer, a system called Rubicon, uses models only on text, then casts the results into tables and hands the rest to a tabular engine. The orchestrator “looks like a query optimizer.” Stonebraker says it is cheaper by a factor of 10 and considerably more accurate than agent frameworks built around a model. He expects agentic AI to slide from the top of the hype cycle into the valley of despair before a more balanced view emerges. Enterprises hate non-determinism: Approve a loan and reverse it on review, and “that’s called a lawsuit.” Organizations also need protection from rogue agents. The guardrails inside the database, he notes, largely exist already: decades of access control, complete logs, and triggers that can stop a transaction in its tracks. Data-heavy agents, he suggests, belong inside the data layer as user-defined functions, if the tooling to debug and version them improves. Stonebraker is equally blunt about the frontier. The models have already used the real training data on the internet, and he knows of no enterprise that will let a model train on its proprietary data. AGI, he said, is “basically marketing hype” from foundation model vendors justifying their valuations. Nobody owns it Why Postgres? “Postgres is the intergalactic answer to open source,” Stonebraker said. Its unique feature is that “it’s not controlled by any one company.” EDB, Microsoft, Google, and others each contribute committers, and nobody steers. He dates its rise to Oracle buying MySQL, when “everybody said: vendor control.” For enterprises, that independence is the foundation of sovereignty: retaining control over how and where their data systems operate. Momjian describes the same structure from the inside. Postgres has no office, no assets, and no legal entity, yet it produces “software better than billion-dollar companies.” Its forecasting tool is the community itself, which spots needs early from China, Russia, and the United States. “We only need one person in the world to be supersmart, and that person to tell us what they think.” Built to bend Both experts describe a design philosophy that favors flexibility over the last few percent of speed. Stonebraker built Postgres to be extended, and that is why it absorbed JSON, full-text search, GIS, and now AI without a rewrite. Momjian adds a second call from the 1990s: Lean on the operating system rather than absorb it, which made Postgres a natural fit for the cloud. Momjian resists optimizations that buy 5 or 10 percent at the cost of rigidity, since a mistuned system can lose 40 percent. “If you take a Formula One car to the supermarket, there’s no place for the groceries.” The project plans on a horizon few vendors can match. “We’re looking at what would be the impact 5 years from now, 10 years from now.” What PostgreSQL 19 delivers The new release puts that discipline on show. Several previewed features, including SQL property graph queries and partition merging and splitting, were reverted, because reliability comes first. AI-assisted review is finding problems quickly; the August 2026 patch release for PostgreSQL 18 addressed 28 CVEs. What remains is practical: REPACK CONCURRENTLY for busy tables, smarter parallel autovacuum, and sequence synchronization for logical replication. Plan Advice, from PostgreSQL major contributor and committer Robert Haas, is the community’s answer to Oracle-style optimizer hints it rejected for years. “Somebody found a way of doing it that didn’t have the downsides,” Momjian said. The database as AI’s memory The two diverge on how fast AI will write SQL. Momjian expects agents to create databases and generate much of the code. Stonebraker says that will not happen inside the enterprise until data is documented, silos are opened, and the politics change. They agree on the destination. AI needs a relational system to give it permanence and memory, and, in Momjian’s words, that is “a game-changer.” Forty years on, the inventor and the steward are betting on the same database. Contributed by EnterpriseDB

De zaak uit 2023 draait om een man die zich verzette tegen zijn aanhouding. Het is een unieke strafzaak: nooit eerder werden zoveel politiemensen vervolgd wegens het onjuist aanwenden van geweld. Uiteindelijk draait het om de grenzen van het geweldsmonopolie van de politie.

MONTREAL (ANP) - Voorzitter van de Europese Commissie Ursula von der Leyen ziet Canada als partner in de handelsstrijd die momenteel wereldwijd wordt gevoerd. Dat zei ze op de eerste dag van de top tussen de EU en Canada.

Von der Leyen noemde geen specifieke landen als tegenstanders in de handelsstrijd, maar had het wel over leveranciers van "energie, halfgeleiders of kritieke grondstoffen" die hun producten gebruiken als drukmiddel. Daarmee lijkt ze te hinten op China en de Verenigde Staten.

"Wanneer handel wordt gebruikt als instrument voor economische druk, zijn het de gezinnen die daar de prijs voor betalen", zei ze. "We zien hier in real time hoe onze soevereiniteit wordt aangevallen."

Von der Leyen denkt dat de EU en Canada elkaar daarin kunnen helpen. "Neem bijvoorbeeld kritieke grondstoffen: Canada beschikt over rijke natuurlijke hulpbronnen en diepgaande expertise in de mijnbouw, terwijl Europa de industriële vraag, technologie en investeringskracht inbrengt. We vullen elkaar aan."