Much of this reads like what the Democrats’ strategy has already been for the last 10 years or so with some additional calls towards a “moderate” “centrism” that has not proven to be as popular as left populist policies with most Americans. And a lot of it seems confused or just wrong. For example, Medicare for All is not an unpopular policy. Last I checked it it was polling at around a 60% approval.
Even if your politics are more centrist, I don’t see how this represents a substantive shift in any way. It’s minor tinkering around the edges or slightly altering messaging. That’s what the moment calls for? That’s the key to success and the way to fight back against an increasingly overt and ascendant strain of fascism in the country? If that’s what the Democratic leadership thinks then one must honestly wonder if the party is institutionally incapable of the change that would need to happen to actually win elections and improve their godawful approval ratings. And based on their donor base, this shouldn’t actually be surprising. The leadership is still utterly captured by and beholden to wealthy interests that would rather jump off a bridge than acknowledge that what Americans want is a party that will fight for meaningful material benefits in their standard of living as this implies meaningfully raising taxes and imposing costs or regulations on their businesses to ensure benefits for regular working class people who are struggling mightily.
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My biggest takeaway here is that choosing the context length and (to a lesser extent) the temperature carefully is important for reducing hallucinations. I expected model families to vary widely between themselves but not for context length to have such a massive impact tbh.
It seems from this like reducing context length in applications where it isn’t essential for the model to hold very large amounts of context simultaneously would be best practice no?