Tencent is seeking this type of engineer for its artificial intelligence division. According to Xataka, its listings on the Boss Zhipin job platform offer between 35,000 and 65,000 yuan a month, with fifteen salary payments. At the upper end, that is 975,000 yuan a year. The scale stands out against the salary benchmarks cited
Does blocking AI training also mean disappearing from search results? Not necessarily.
The practical problem for publishers is that each company used its own crawler name. So, to opt out of several, a site had to maintain separate rules. And the shared signal changes how that preference is expressed. That is the intention. Instead of relying solely on a list of rules for
Robots.txt could simplify how websites opt out of AI training. OpenAI, Google, Microsoft, and Anthropic support a shared signal, but adoption and timelines still vary.
AI engineers, Tencent, and salaries of up to 975,000 yuan a year: discover why demand for forward-deployed engineers is growing and what they do to bring artificial intelligence into real work at companies.
Hyperion, Meta, and $27 billion in debt: who bears the risk of financing data centers for artificial intelligence? Follow the money behind the project in Louisiana.
A vague coding request can hide a whole chain of work.
A coding agent scores 57.8 percent on CursorBench. Another configuration of the same model scores 56 percent. The first costs an average of 13 dollars and 43 cents per task; the second, 3 dollars and 97 cents. That is a small gap in score and a much larger gap in cost. What are the agents being asked to do? Cursor says
Alphabet fell 12.64% in a single session. Intel lost almost 30% at one point the following day. The two declines have different causes, but the Cinco Días editorial reads them as signs of the same demand: the stock market wants to see revenue and profits capable of sustaining the enormous spending on artificial intelligence. Let’s begin
Artificial intelligence puts the stock market to the test: declines in Alphabet and Intel reignite the debate over investment, profits, and the risk of a bubble.
CursorBench 4.0 tests coding agents on ambiguous, multi-file tasks. Opus 5.5 Max scores 57.8%, while Opus 5.5 High scores 56% at less than a third of the average cost per task. What does that small score gap really tell us?
Ninety thousand tables sounds like a search problem. But that number does not tell us how many tables an AI agent actually checks.
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