According to you. That's not the opinion of every prospective employer. Hedging is the right strategy.
6,340 karma · joined May 9, 2017
According to you. That's not the opinion of every prospective employer. Hedging is the right strategy.
I can think of a lot of positives. The negatives amount to a convoluted argument about the limits of free speech.
Probably worth a watch if you enjoy the genre. If you’re someone who just enjoys a good story, this is a pretty easy skip.
The future of air superiority, particularly with respect to sovereign defence is passive or quantum radar, autonomous A2/AD and directed energy.
The simplicity of JSX is overvalued. It just means more code, and typically uglier code, to achieve the same behaviour as Vue. Which is basically the theme of React when you compare the two libraries.
Please explain React’s reactive data binding since it’s apparently much simpler than v-model=
;)
It does have its own templating syntax, which is trivial to learn. No more cumbersome to learn than JSX, which is a templating language designed by the React team. Not sure why you chose to make the distinction between JSX and Vue’s DSL as if JSX wasn’t developed for the sole purpose of facilitating React’s virtual DOM.
- Breaking down a problem into a planned execution, with executing agent providing the initial plan which includes explicit objectives such as which tools it calls and what it would consider to be a successful execution.
- The harness then executes the plan in order
- Each step that involves a tool call will be executed by breaking down the tool call into component parts: the harness interrogates the agent for a valid parameter value for the current tool argument. The tool definition contains validators for each argument. If the validator fails, the harness rewinds the conversation and injects the failure reason into the next try.
- Once the agent produces a valid response for the argument, the harness proceeds to the next argument.
- Once all the arguments have been filled, the harness calls the tool. It passes the agent's initial expected value along with the actual value, along with any errors that may have been produced and asks the agent if it is satisfied with the result. If it isn't, the agent provides a reason and the harness then retries the tool call process from the beginning rewinding the conversation and inserting the reasoning for the retry.
- The agent may request to re-plan if it discovers a flaw in its initial plan. The harness will also attempt to re-plan if the agent produces too many failures in a row.
This proves to be quite effective at reducing tool call failures. One benefit is that the sub-agent gets a perfect conversation history where it makes no mistakes. I'm not sure if it's actually better at completing tasks though, I haven't tried to benchmark it.
A crow exhibits some degree of intelligence in what is a very small brain compared to humans. There is overlap in the problem solving skills of the dumbest humans and the smartest crows.
So the question is: what is that? Yann LeCun seems to think it’s what we now call world models. World models predict behaviour as opposed to predicting structured data (like language.)
If your model can predict how some world works (how you define world largely depends on the size of your training data), then in theory it is able to reason about cause and effect.
If you can combine cause and effect reasoning with language, you might get something truly intelligent.
That’s where things seem to be going. Once we have a prototype of that system, there will be many questions about how much data you really need. We’ve seen how even shrinking LLMs with 1-bit quantization can lead to models that exhibit a fairly strong understanding of language.
I don’t think it’s unreasonable to expect to see some very intelligent low (relatively) memory AI systems in the next couple years.
I still kind of think it’s a decent idea but it’s too close to MCP with drawbacks that make it a harder sell than MCP. It’s hard to compete on functionality from a secure sandbox if users decide they don’t care about security.
Your example is already under dispute by actual humans. Expecting non-AGI to get it right is not realistic.
And that’s the same as censoring a country’s violent history to you guys?
How intellectually dishonest.
https://i.imgur.com/cVtLuj1.jpeg
The absence of information is also Xi Jinping Thought.
If you invest anything in the Canadian market you probably hold some Brookfield.
Carney’s investments are in a blind trust.
What more could be done, in your view?