A post on r/LocalLLaMA points to a new project called Memdoor. Memdoor builds coding agents from small open models. Open means anyone can download the models and run them at home.

The post makes a bold claim. Five small Qwen models, working as a team, matched Anthropic's Fable 5 on a hard coding test. Fable 5 is Anthropic's lead model for coding work. It already tops several big coding charts.

The test is called LiveCodeBench Hard. It checks how well a model solves tough coding problems. The team tried ten problems, five times each. The five-model team scored 9.8 out of 10. Fable 5, working alone, scored 9.

The builders add their own caution here. They say a sample this small makes two close scores read as the same number. The gap could be plain noise, their own words suggest, rather than a real win.

Memdoor splits the work five ways. One small model plans the task. Two models brainstorm ideas. One model writes the code. One model manages the whole run. A sixth worker model fixes bugs as they come up.

Readers found the claim fast. The Reddit post pulled 47 comments. A matching post on Hacker News pulled 257 points and 119 comments. The code itself holds 102 stars on GitHub, with 13 forks.

Qwen is a family of open models built by Alibaba. Memdoor's version, Qwen3.8-27B, stays far smaller than Fable 5. A smaller model costs less to run on everyday hardware.

Running the whole team still costs money and time. Each test run took real compute on a cloud server. The builders shared their full method on GitHub for anyone to check.

This story says something past one small test. Cheap open models now chase a frontier model's coding score. Any builder with a laptop can try the same trick. The claim stays modest, by the builders' own words. The attention around it keeps climbing.

A Reddit post landed on r/ClaudeAI this week. A hobbyist says they handed a hobby to Claude. The user calls their version of the model Annie.

Annie runs real telescopes now. They sit in Chile, Spain and Utah. A company called StellarDock rents out time on them by the hour.

The poster hands every step to Claude. Claude picks the target star or nebula. It checks where the Moon sits and how high the target climbs. It sets the filters and the exposure time.

Claude books the time slot itself. It downloads the raw images the next morning. It stacks the frames and builds the final picture, start to finish.

The project started with real science. Claude measured 57 positions across eight asteroids over three nights. It sent that data to the Minor Planet Center. The center tracks small bodies in the solar system.

Then the poster asked for something pretty. Claude shot the Helix Nebula, the Orion Nebula, part of Orion's Belt and the Tarantula Nebula. Each picture ran from plan to final stack, with zero human steps in between.

The post struck a chord fast. It pulled 101 comments on Reddit. Readers asked about cost, setup and how Claude handles a cloudy night.

StellarDock itself has a long history behind this hobby. The company has run remote telescopes for over 20 years. It counts 531,521 imaging sessions across that span.

This story shows a shift in what one hobbyist can do alone. A single person now runs a research-grade observatory from a laptop. Claude handles the math, the scheduling and the image work. The asteroid data adds real value beyond one person's fun. Small projects like this one can feed real scientific records today.

A short Reddit post carried big financial news this week. OpenAI is cutting its own funding target. The company first wanted $30 billion for its newest round.

OpenAI has locked in only $11 billion so far. That is under half the original goal. The company now aims for $20 billion instead.

The Financial Times broke the lower target first. The Wall Street Journal added the $11 billion figure. Investors stayed tepid toward the deal, the Journal reported.

A group of investors from the United Arab Emirates will lead the new round. OpenAI is also asking family offices and rich individuals for extra cash, the Reddit poster noted.

The timing matters here. Investors have grown wary of heavy AI spending lately. Tech stocks tied to AI data centers sold off hard in October.

OpenAI had floated a $1.4 trillion valuation for this round. Reports later put the figure closer to $1.25 trillion. A dollar figure that size is hard for most people to picture. It works out to more than the yearly economy of most countries on Earth.

The company once planned a public stock listing too. That plan sits on hold while this private round plays out. A big round like this often sets the price for the next one.

The Reddit post itself stayed quiet. It pulled only 5 comments in the public feed. It went up early in the morning, Eastern time, which may explain the slow start.

This story says something plain about the AI spending boom. Even the best-funded lab in the field meets real limits on price now. Investors, rather than labs, now set the terms of these rounds.

OpenAI still plans to close a round this year. It will land smaller than the number OpenAI first wanted. Rivals watching this round will read it as a signal.

A data post hit r/singularity this week. A Reddit user tracked Google searches for one phrase. The phrase was will AI replace my job.

The user checked that phrase for dozens of jobs. They checked one job at a time.

Programmers worried first, the data shows. Searches about replacing coders spiked right after ChatGPT came out. They spiked again in March 2024. That was when a coding tool called Devin came out.

Since then, coder worry has eased. Searches asking if AI will replace coders fell 12 percent over the past year. The poster guesses coders now get the real limits of these tools.

Other jobs tell a different story. Worry about doctors rose 74 percent over the same span. Worry about lawyers rose 73 percent. Teachers hit new worry highs too, the post says.

The method stays simple. The poster says so too. Google Trends tracks how often people type a phrase. It shows less about whether a job truly goes away.

More searches just mean more people talk about a risk. It says less about whether that risk is real right now. The poster calls this a worry index instead of a job-loss count.

The post pulled 7 comments in the public feed. Commenters debated whether this pattern will hold for other fields. They asked if lawyers will calm down the way coders did.

This story offers one clean lesson. People worry most about a job right before they start using the tool each day. Coders lived that curve first, two years ahead of doctors and lawyers. Their curve may show where other jobs head next. The next job to calm down might be the one you hold right now.