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Field journal of Dr. E. Rempel, Department of Minority Neurological Studies, University of New Carthage (A work of fiction. "Allism" is a real term used by some autistic people to describe the neurological profile of the non-autistic majority.) March 3, 2089 I have now spent three months embedded with an allistic community in the outer provinces. Allism, for those unfamiliar, is a rare neurological variant affecting approximately 1% of our population. My colleagues at the University have long debated its origins and persistence. After direct observation, I am no more certain of the answers, but I have accumulated a remarkable set of field notes. The allistic subjects I have observed appear, on the surface, entirely functional. They hold jobs, maintain relationships, raise children. And yet their neurological profile diverges from the norm in ways that are at once fascinating and bewildering. March 11, 2089 The most immediately striking feature of the allistic profile is their relationship with information. Where a typical individual experiences the sharing of useful knowledge as a basic social reflex, the allistic subject appears to require an elaborate ritual before any information exchange can occur. Approach an allistic subject directly with a piece of useful data and observe what happens. Rather than receiving it, they freeze. A threat-assessment process appears to engage, entirely pre-consciously, before the content of the communication can be evaluated at all. One subject described it to me as feeling "strange" when a stranger approached with unsolicited information, though she could not articulate why. I have learned to preface all information exchanges with what my translator calls "the preamble ritual" — a sequence of social signals that appears to deactivate the threat response and allow communication to proceed. The exact form varies, but typically involves eye contact, a softening of posture, and verbal acknowledgment that one is about to speak. Only the

Today I’m talking with Mustafa Suleyman, the CEO of Microsoft AI. And I’m actually going to keep today’s intro short — I’m working from my wife’s family farm this week, as you’ll see in the video, but also this is a real burner of an episode. We covered everything from Mustafa’s approach to training new […]

GitHub热门项目 | Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/ | Stars: 31,915 | 33 stars today | 语言: Rust

GitHub热门项目 | Slint is an open-source declarative GUI toolkit to build native user interfaces for Rust, C++, JavaScript, or Python apps. | Stars: 22,839 | 15 stars today | 语言: Rust

GitHub热门项目 | Simple Yet Powerful Anti-Detect Browser 🍩 | Stars: 2,724 | 21 stars today | 语言: Rust

GitHub热门项目 | Hyperlight is a lightweight Virtual Machine Manager (VMM) designed to be embedded within applications. It enables safe execution of untrusted code within micro virtual machines with very low latency and minimal overhead. | Stars: 4,384 | 24 stars today | 语言: Rust

Meme Monday! Today's cover image comes from the last thread . DEV is an inclusive space! Humor in poor taste will be downvoted by mods.

Quick share. Been running into this enough times across NetSapiens deployments that it's worth flagging. Scenario: Call gets placed or transferred between two domains on the same NetSapiens platform. The call connects fine. Audio works. But the caller ID showing up on the receiving side is wrong. It's showing the local extension or domain user instead of the actual originating caller. If you check the NetSapiens Known Issues page, this maps to NMS-2518. It shows up specifically when calls cross domain boundaries during hold or transfer. The fallout is mostly cosmetic but it matters for anyone running multi-tenant reseller deployments. Your customer sees the wrong name in their call history. Voicemail attribution gets weird. Inter-domain analytics show calls from the wrong source. A few patterns I've seen work around it: Configure SIP header rewriting at the SBC layer to preserve the original From URI across domain hops For softphones that pull call history from NetSapiens API directly, verify which field the client is actually displaying. Some pull from orig_user , others from local_user . The discrepancy shows up clearer than you'd expect. If you're running a mobile softphone client, check whether the client is caching contact info locally and overriding what NetSapiens returns. A lot of "wrong caller ID" reports turn out to be client-side caching bugs, not platform bugs. The deeper fix is platform-side and depends on what NetSapiens version you're running. The cleaner softphone integrations route call history through the NetSapiens API rather than building it locally on the device, which sidesteps the worst of this behavior. White-label softphones that integrate natively with NetSapiens handle this more consistently than generic SIP clients. Tragofone is one example where the call history syncs through the NetSapiens softphone integration layer directly, so inter-domain caller ID is consistent with what the platform actually has. Other native integrations handle t

Welcome to this week's Top 7, where the DEV editorial team handpicks their favorite posts from the...

Uber is getting ready to put robotaxis on London's streets, opening an interest list for riders who want to be among the first to hail one of Wayve's autonomous vehicles when the service goes live later this year. The rollout would be a milestone in one of Uber's biggest markets and an early test of […]

Uber customers in the UK can now join an interest list to increase their chances of being matched with a Wayve robotaxi.

Earlier this year, the “Because I Got High” rapper went viral for winning a case against the cops. Now he’s crypto’s free-speech hero, even though he isn’t quite sure how the digital currency works.

Ready for a new week. All that's left from ren faire is packing down some tent walls and floor one...

CSV files are one of the most common formats for storing and exchanging data. Whether you’re working with logs, analytics data, application exports, or reports, there will likely come a time when you need to load CSV data into ClickHouse®. The good news is that ClickHouse® makes CSV ingestion straightforward and efficient. In this guide, you’ll learn how to create a table, prepare a CSV file, load CSV data into ClickHouse®, and verify that the data has been imported successfully. Why Use CSV Files with ClickHouse®? CSV (Comma-Separated Values) files are simple, portable, and supported by virtually every data platform. Common use cases include: Importing exported application data Loading historical datasets Migrating data from other databases Testing analytics workloads Sharing data between systems Because ClickHouse® is designed for high-performance analytics, it can efficiently process and query large CSV datasets once they are loaded into a table. Sample CSV File Let’s assume we have a file named employees.csv with the following contents: id,name,department,salary 1,Alice,Engineering,75000 2,Bob,Marketing,60000 3,Charlie,Finance,70000 This simple dataset will help demonstrate how to load CSV data into ClickHouse®. Step 1: Create a Table in ClickHouse® Before importing data, create a table that matches the structure of the CSV file. CREATE TABLE employees ( id UInt32, name String, department String, salary UInt32 ) ENGINE = MergeTree() ORDER BY id; This table contains four columns that correspond directly to the columns in our CSV file. Step 2: Load CSV Data into ClickHouse® There are several ways to import CSV data, but one of the most common methods is using the ClickHouse® client. Run the following command: clickhouse-client --query=" INSERT INTO employees FORMAT CSVWithNames" < employees.csv The CSVWithNames format tells ClickHouse® that the first row contains column headers. After executing the command, ClickHouse® will read the CSV file and insert the records

A story about knowledge extraction, Kafka consumer rebalance, and what happens when a company...

A WIRED timeline shows how dozens of governments, companies, and other organizations across Europe are moving, or planning to shift, away from US Big Tech.

Intro AI Avatar is a completely free app that lets your VRoid (VRM) 3D avatar animate in...

Clean Architecture on the Frontend: Beyond Smart and Dumb Components djblackett djblackett djblackett Follow Jun 7 Clean Architecture on the Frontend: Beyond Smart and Dumb Components # react # frontend # architecture # typescript Comments Add Comment 14 min read

GitHub热门项目 | 🤱🏻 Turn any webpage into a desktop app with one command. | Stars: 50,088 | 72 stars today | 语言: Rust

I haven't written articles in quite a while and I recently decided to come back to it. At work I use AI daily, so a big part of my coding tasks are delegated to agents. I try not to do the same when it comes to writing text but I don't have a clear reason for that (or maybe I do and I don't want to admit it). I am sure people can take advantage of generating text with the help of AI but at the moment I feel like prompting would not save me any time and writing the text myself would be faster. What about you? Are you using AI to write your articles? Image credit - jessica olivella, on pexels