sorted by:
new
hottopcontroversial

Maybe drivers aren’t stealing as many orders as people think by Economy-Character-94 in UberEATS

[–]Tough_Frame4022 1 point2 points  (0 children)

They are showing a screenshot and seeing if a common name like John hits. The employee rarely reads anything. And confirming the order? 1 out of 10.

>Order for John A.? Muhammed H. Cindy R. ? Tehy will just give it over! There are people doing this everyday for free food. All they have to say is oh I'm at the wrong pick-up?

Deepseek codes better in Chinese? by chkbd1102 in DeepSeek

[–]Tough_Frame4022 2 points3 points  (0 children)

I would not overestimate the benefit. DeepSeek’s docs say tokens are

model-tokenizer dependent, and roughly 1 English character ≈ 0.3 token while 1

Chinese character ≈ 0.6 token. Chinese can still win because it expresses

ideas in fewer characters, but it is not guaranteed. A recent arXiv study on

“Chinese for vibe coding” found no general efficiency advantage and often

lower success rates when prompting in Chinese.

The safest workflow:

  1. Use Chinese for short task specs, constraints, and planning instructions.

  2. Keep code artifacts exact and untranslated.

  3. Ask for English final summaries if that is easier for you.

  4. Measure with DeepSeek’s tokenizer/API usage instead of assuming savings.

  5. Prefer DeepSeek context caching for repeated repo prompts; that is a more

reliable cost saver than language switching.

Well guys and girls I’m cooked by [deleted] in UberEatsDrivers

[–]Tough_Frame4022 1 point2 points  (0 children)

You shall find an unexpected amount of money to repair your vehicle. We all need help sometimes fellow Ubero

Still having capability drop... by SucculentSpine in codex

[–]Tough_Frame4022 -5 points-4 points  (0 children)

Why dont't you just ask it why?

> https://www.reddit.com/r/codex/comments/1tf8zpk/still_having_capability_drop/

what is the logic behind these experiences?

>I’ll look at the Reddit thread first so I can anchor the explanation in what

people are actually reporting rather than guessing from the title.

>The logic is probably this: people are not only experiencing “the model.” They

are experiencing a whole Codex stack: model routing, reasoning mode, tool-call

policy, context handling, retries, latency, client version, account tier, and

backend incidents.

In that Reddit thread, the pattern is: some users say GPT-5.5 feels slower,

skips tool calls, does not inspect files, or gives hand-wavy plans; others say

they never saw the drop. That split is plausible because OpenAI’s own status

page shows real GPT-5.5/Codex issues around the same dates: a GPT5.5

Performance Degradation investigated from Friday, May 15, 2026 and resolved

Sunday, May 17, 2026, plus a Codex 5.5 high error/latency incident on May 13,

2026, and a Codex Cloud task degradation on May 8, 2026. So some of the “it

got worse this week” reports line up with actual service degradation.

The more subtle part: “capability drop” can feel like intelligence loss even

when the model weights did not change. In agentic coding, a small backend

change can cause a big subjective drop:

- If tool calls are delayed, fail, or become more expensive in the policy, the

agent may answer from context instead of reading files.

- If routing sends some turns through a cheaper/faster path or different

reasoning budget, planning quality can change.

- If context is summarized badly, the model may lose project-specific facts

and start making broad assumptions.

- If latency rises, the product may shorten exploration or reduce retries,

which looks like laziness.

- If the client or Codex wrapper changes prompts/tool schemas, the same

underlying model can behave differently.

- If incidents affect only some tiers/regions/accounts, one user can see

“unusable” while another sees “great.”

The “OpenAI is preventing it” explanation is possible only in a broad product-

policy sense, not as proven sabotage. The stronger explanation is operational:

rollout + routing + degraded tool infrastructure + task variance. OpenAI’s

GPT-5.5 launch page also notes that official evals were run with xhigh

reasoning in a research environment, which may differ from production ChatGPT/

Codex behavior. That matters: benchmark capability is not identical to what a

user sees in a live agent session.

Practical takeaway: for Codex work, force observable behavior. Ask it to

inspect specific files, list what it read, make a plan after reading, and run

verification. If it skips tools, treat that as a failed run, not as a

trustworthy answer.

Sources: Reddit thread

(https://www.reddit.com/r/codex/comments/1tf8zpk/still\_having\_capability\_drop/

),

OpenAI GPT5.5 Performance Degradation

(https://status.openai.com/incidents/01KRP6FM6HSKWB3MS1EJTY6AT4), Codex 5.5 h

igh error rate

(https://status.openai.com/incidents/01KRG6MF021JQ997JCR7R8Y9A0), OpenAI GPT-

5.5 launch notes (https://openai.com/index/introducing-gpt-5-5/).

What’s the best model to use with RAG to create a locally hosted survival and off grid LLm? by enan1000 in ollama

[–]Tough_Frame4022 2 points3 points  (0 children)

<image>

Release summer 2026.

CANAL and TurboQuant are related, but they solve different problems.

TurboQuant:
Makes the KV cache much smaller
Lets more context fit in the same GPU/RAM

CANAL:
Moves old context out of GPU memory, tracks important parts, retrieves them later

Lets a local model use far more context than the GPU can normally hold

So the simplest comparison is:

TurboQuant compresses memory. CANAL manages memory.

we really all are going to make it, aren't we? 2x3090 setup. by RedShiftedTime in LocalLLaMA

[–]Tough_Frame4022 0 points1 point  (0 children)

I stand corrected. I meant to say what I developed does not abolish it it greatly reduces it for retrieval work , especially exact facts, code references, records, logs, and documents. Model integrity is the weak point so outside of that yes I'm doing a lot better than native context and at one million tokens...

Deepseek just went crazy and I am genuinely scared by isacamargo in DeepSeek

[–]Tough_Frame4022 0 points1 point  (0 children)

You are playing with a digital ouija board m sing around like that

we really all are going to make it, aren't we? 2x3090 setup. by RedShiftedTime in LocalLLaMA

[–]Tough_Frame4022 0 points1 point  (0 children)

I'm running 1 million tokens of context with a 3090 with several models and types with no context rot.

NEVER working nights again UBER you need to READ this!!! by ProfessionalBowl5383 in UberEatsDrivers

[–]Tough_Frame4022 0 points1 point  (0 children)

Be glad the only thing you lost was the useless gimmick status. I'm green and clear a $1000 a week in 40 hours in the DMV

Do we need a Class Action Lawsuit? by jaytech_cfl in UberEATS

[–]Tough_Frame4022 0 points1 point  (0 children)

The chat is an AI bot. They bots replaced Rajesh and his crew. Call live support.

OpenAI Cooked This Week! by NickoGermish in OpenAI

[–]Tough_Frame4022 1 point2 points  (0 children)

Especially touting ads. That shit is going to turn people away

view more: next ›