gavinray
It sounds autistic, but writing and reading allow you to be much more precise, careful, and deliberate with your words and helps reduce impulsive outbursts.
This has worked really well for us, as crazy as it sounds.
This sort of throws a wrench in the whole "stochastic parrot" idea...
I am not surprised, though I expect many to be.
I've worked with a lot of outsourced development/contractors in my time. Consistently, the best experiences have been with Eastern Europeans.
If not, Seattle/Bellevue are a great option. Or Portland even.
I was told that there are rent-subsidy programs that allow people making relatively low wages to pay e.g. $300-800/mo for a 1-bedroom apartment
My thought after hearing that is that, unless you're making north of $300-400k, it's probably better to make around $50-60k and collect subsidies + benefits. The middle income group gets shafted.
I actually prefer 4-AcO because it's easier to get a consistent dose with (mushrooms vary in potency) and doesn't cause the nausea that consuming dried mushrooms sometimes causes.
The demand for compute for AI is increasing, why would a compute producer lose value?
One of the only surviving darknet markets only takes Monero as currency.
Make of that information what you will
Being denied housing or employment was not just a regular occurrence but the norm for me for a large portion of my life
I recall seeing a project based on DuckDB parser and engine which emulated dialects for one of these but because the sortinh and other behavior is different it wasn't usable
> "a just society should generally tolerate the intolerant, reserving self-preserving actions for only when intolerance poses a concrete threat to liberty and stability."
If intolerance or hate poses a physical threat, or in any way infringes on the liberty and personal autonomy of others, a line has been crossed and must be swiftly dealt with.
Should you be racist? No. Should you call someone fat and ugly? No.
But personal liberty and freedom require we allow people to make choices and have opinions we don't personally agree with.
For example: Suppose you hire someone to help you move furniture.
You can decide you dont like the color of their shoes and tell them to kick rocks.
You dont owe anyone a job, and labor for pay is a contractual agreement, nothing more.
Our connectors receive a generic query IR from a Datafusion-based engine
Each connector is then responsible for faithfully translating the query IR into the semantically equivalent query for the underlying data source
For a SQL DB this would be a SQL query, for MongoDB a JSON predicate query, for csv/json files it would be an in-memory predicate engine, etc
Running the generated query against the target data source and asserting that this doesn't throw an error and that the records returned are both correct and in the right order is the true test
I could imagine in British English it might be a two-syllable "poh-ehm" though
1. Sleep debts effect on muscle size and strength gain
https://share.gemini.google/Gvdb5Q02INrl
2. Fish oil and extra cellular vesicles
https://share.gemini.google/fem9EBCe4mfy
3. Pharmacology question about human-equivalent dose
Especially with the recent addition of graphic visualization widgets
It manages to strike the perfect balance between depth and style of prose that other Frontier models just can't quite seem to match
> "Nix is lazy, so the emitted code wraps an expression in nix.thunk(() => ...)"
On-demand value materialization is what Generators are for
> pgVolvra records every row change on the tables you choose. For each change, it keeps the row as it was, and the row as it became, along with who made the change, when, and in which transaction. When something goes wrong, it uses that record to put the affected rows back, and it touches nothing else.
I'd imagine you could actually build this reusing a lot of the existing WAL code if you were Inclined
> "add_or_sub_big: Qwenputer scores 97.5%, the same as with a Python tool, and 87.5% for base Qwen."
I'm sorry but I'm not sure I understand how a calculator that isn't 100% accurate is useful?
I work on connectors to various datasources, mostly SQL DB's
The most useful tests are the integration tests, sending actual queries to the source
For most DB's we have a giant Docker Compose which runs a local instance
But things like Snowflake, Databricks, Redshift, Athena suck to test because we need an external hosted instance
I would kill to be able to run test versions of all of these locally
> "Edit this image to color code the benchmarks scores using a gradient scheme that is immediately obvious"
> are they essentially holding back sort of unweighted parameters built in to the model architecture which they can then populate with new context during 'sleep' and then using the techniques outlined in the 'dream' section to reinforce...
They say the weight update can be done by computing a transform where the end state is the old weights with the addition of the useful semantic knowledge contained in memories. Rather than just additively chucking the entire memory concepts into weights. That's pretty neat.
The subtext for the memory architecture diagram sums the whole thing up pretty tidily I think:
> Input streams from the active phase are stored in short-term memory before entering the sleep cycle, which bifurcates into Consolidation (transferring fragile short-term tokens into expanded long-term parametric memory using low-rank structures and MoE) and Dreaming (autonomous self-improvement via synthetic routing with random experts and RL refinement).