AI Weekly Malaysia

Facebook has introduced Facebook Verified, a new, free feature designed to confirm that there is a real human being behind a profile. Using a simple video selfie process, this initiative aims to restore trust and authenticity on the platform amidst the ever-growing AI-generated content and accounts. What’s the difference between Facebook Verified and Meta Verified? […]

Samsung is introducing a much stricter lock screen security policy with its latest One UI 9 that ships out of the box with the latest Galaxy Z Fold 8, Z Fold 8 Ultra and Z Flip 8. If you enter the wrong PIN, password or pattern 13 times, your device will be permanently locked and […]

Forget YouTube videos — frontier physical AI models need multiple camera angles, dense annotation, and, soon, brain wave readings.

As Apple prepares to launch its first smart glasses, the company may also be wrestling with how to address consumer privacy concerns.

On the latest episode of Equity, we discussed why Moonshot AI's Kimi seemed to panic Silicon Valley and Wall Street.

An Inside Look at the Relay Market Powering Token Resellers and Fraud Fascinating investigation by Matt Lenhard into the market that has grown up around reselling LLM tokens at a discount by pooling API keys from various sources. This looks to be mostly a thing in China. Resellers sell access to an LLM proxy that offers significant discounts on regular API pricing, which they achieve by abusing free trials, proxying through unprotected support bots, or sometimes through stolen credit cards or chargeback attacks. The software they are using for these proxies is open source - mostly one-api and its more actively developed fork new-api, both legitimate API proxy products which can be used to load. balance requests across a pool of API credentials. The buyers are seeking cheap tokens, avoiding geo-restrictions, and in some cases collecting data for model distillation. I've been cautious about exposing my own LLM-driven applications publicly out of fear of abuse leading to big token bills. The existence of this marketplace makes me even more cautious: there's now an entire ecosystem that can profit from finding a new unprotected endpoint to exploit. LLM vendors really need to get better at offering strict caps for their API keys. I want my LLM apps to stop working the moment they hit a dollar threshold I've set for a period of time. Here's the (Chinese language) forum thread that served as the principal source for Matt's article. Via Hacker News Tags: ai, generative-ai, llms, llm-pricing, ai-ethics, ai-in-china

How one founder house is betting work-life balance can beat burnout .

"The first autonomous agent cyberattack is an unprecedented event. It deserves an unprecedented response!"

Welcome back to TechCrunch Mobility, your hub for the future of transportation and now, more than ever, the role AI is playing in it.

Listen now | Dianne Penn, Anthropic’s first PM, on the bets that made Claude dominant: the coding pivot, the eval-driven development loop, and what comes after coding is solved

A running look — in reverse chronological order — at the bigger tech companies that have announced significant layoffs this year with AI as a stated factor.

Ruff v0.16.0 Astral shipped a significant new version of their Ruff Python linting tool a few days ago on July 23rd. I noticed today because my various CI jobs all started failing thanks to new default Ruff checks and my unpinned "ruff" dev dependency. From Brent Westbrook's announcement post: Ruff now enables 413 rules by default, up from 59 in previous versions. Since Ruff's default rule set was last modified in v0.1.0, the number of rules in Ruff has grown from 708 to 968. Many of these rules catch severe issues, including syntax errors and immediate runtime errors but were not previously enabled by default. With the new rule set, Ruff will bring these issues and many others to your attention without any Ruff configuration. Here's a one-liner for trying it on any Python project: uvx ruff@latest check . I ran the latest Ruff against my three biggest projects - Datasette, sqlite-utils, and LLM - and it found hundreds of minor issues that breached the new default rules. All three projects have very comprehensive test suites, executed in CI against Python 3.10 through Python 3.14, so upgrades like this are pretty safe. The following command did the bulk of the upgrades: uvx ruff@latest check . --fix --unsafe-fixes Against sqlite-utils, that command reported: Found 1618 errors (1538 fixed, 80 remaining). As an illustrative example, here are three of the remaining issues. Ruff does a nice job of explaining each one: DTZ005 `datetime.datetime.now()` called without a `tz` argument --> tests/test_duplicate.py:17:10 | 15 | "datetime_col" TEXT)""") 16 | # Insert one row of mock data: 17 | dt = datetime.datetime.now() | ^^^^^^^^^^^^^^^^^^^^^^^ 18 | data = { 19 | "text_col": "Cleo", | help: Pass a `datetime.timezone` object to the `tz` parameter BLE001 Do not catch blind exception: `Exception` --> tests/test_plugins.py:16:12 | 14 | db.execute("select * from pragma_function_list()") 15 | return True 16 | except Exception: | ^^^^^^^^^ 17 | return False 18 | finally: | B018 Found useless attribute access. Either assign it to a variable or remove it. --> tests/test_update.py:46:5 | 44 | def test_update_invalid_pk(fresh_db, pk, update_pk): 45 | table = fresh_db["table"] 46 | table.insert({"id1": 5, "id2": 3, "v": 1}, pk=pk).last_pk | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ 47 | with pytest.raises(NotFoundError): 48 | table.update(update_pk, {"v": 2}) | Unsurprisingly, given Astral's new home at OpenAI, this output provides everything a coding agent would need to fix the problems. I had Codex (GPT-5.6 Sol high) upgrade LLM and sqlite-utils, and Claude Code (with Opus 5) upgrade Datasette. Tags: python, ruff, astral

The lawsuit will likely renew debates about whether term employment agreements are enforceable under California law.

An awe-inspiring hacktivist who hacked two controversial government spyware makers may be the most prolific hacker to have never gotten caught. What do we know about Phineas Fisher?

Elon Musk's tunneling startup is reportedly in talks for a major new funding round.

Kalshi claims the trailer is “defamatory” and contains “both fabricated documents and false and misleading statements.”

In an ambitious reset, Ashran Ghazi pushes commercialization beyond traditional innovation programmes Bets success on delivering an Innovation District Model that focuses on actual ecosystem outcomes Malaysia has long aspired to become an innovation-driven economy, with tens of billions of ringgit invested over the years in research and development, startups, grants, and digital initiatives. However, translating these ideas into scalable businesses and nationally impactful industries has often proven more difficult. Under the 12th Malaysia Plan, the government allocated approximately RM3.2 billion to research and development across various sectors. Yet, according to reports and studies, the rate of commercialisation has fallen short of expectations. That is the gap MRANTI now wants to address. Make no mistake, it is a huge challenge. During a media briefing in May at MRANTI Innovation Park, Bukit Jalil, Ashran Ghazi (pic), MRANTI CEO who came on board in Dec 2025, laid out a broader vision for the agency. It was about repositioning MRANTI as a national innovation orchestrator focused on commercializing technology and aligning ecosystems. “MRANTI is not a programme. It is an accelerator for the commercialisation of technology,” Ashran said during a media briefing session. “It is a replicable system where every stage is designed to lead.” MRANTI was formed through the merger of MaGIC and Technology Park Malaysia (TPM) in Nov 2021. Under its current direction, MRANTI appears to be moving beyond its role as a technology park operator. It is aiming to build what Ashran repeatedly described as a “Mission-Driven Innovation District”, where national problems are solved through living, working, testing, and scaling together. Before any of these activities bear fruit, taking check of what MRANTI has achieved between 2022 (since it was established in Nov 2021) and 2025 – during which time it was led by Dzuleira Abu Bakar (April 2021- Sept 2023) and Dr Rais Hussin (Oct 2023- Sept 2025) – and based on data shared MRANTI, the agency said it recorded a cumulative economic impact of US$409 million (RM1.675 billion) through investments, revenue creation, and ecosystem partnerships facilitated across its initiatives. It did not share the formula for how it came up with the amount. Over the same period, 7,394 startups, universities, and SMEs participated in MRANTI-linked accelerator programs, commercialization initiatives, funding facilitation efforts, and innovation platforms. No details are available of the impact of these engagements. The agency also launched 16 innovation sandboxes under the National Technology & Innovation Sandbox (NTIS) initiative to help companies test technologies in real-world environments before scaling commercially. Moving beyond programs Ashran noted that research Institutes, universities, corporates, and startups are all working on innovation, but that the vast majority of efforts still happen in silos. And when go

Community Wisdom 194

At libraries around the country, "Avoiding AI" workshops have elicited unprecedented demand.