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Comment by nine_k | Hacker News Reader

Can there be "smart toys" for models that help them self-improve in a particularly efficient way?

A Young Lady's Illustrated Primer

In RL literature this is generally called "curriculum learning".

The curriculum is usually modeled as some form of reward function to steer learning, or sometimes by environment configuration (e.g. learn to walk on a normal surface before a slippery surface).

Yes, the smart toys are search, code execution, simulations and games.

video games are basically like this, progressive level require more skill, learned from the easier levels.

And this is a reason we play video games? That they appeal to some ancient instinct to improve?

Rather, I think it’s borne of necessity to onboard you to the game mechanics. We certainly have a bird brained instinct to catch the worm / win a round, so a good game design cuts you some slack to begin with, so you can have a little dopamine as a treat

From there, difficulty should scale up so you don’t always win, giving you that “intermittent reinforcement“ that makes games addictive

One of the reasons. I'd wager this is what appeals to people not merely playing but mastering a particular game - playing higher difficulties, 100% completion, and so on.

The other reasons would be overcoming other humans (esports/pvp multiplayer), discovery (story driven and exploratory games), and just passing the time (casual games).

I'd say it's feedback/reward loop plus small, quick to achieve, progressive goal setting.

I'm creating "smart toys" like that for humans. I recently launched a mobile app. I'd love to see these research breakthroughs feed back into human learning because if humans remain foolish, the world could fall apart.

With DeepSeek R1 and these autonomous driving research results, it feels like we've entered an era where human data is no longer necessary. The ability to infinitely expand learning through simulation while maintaining safety in the real world feels like science fiction coming to life—it's truly exciting.

Can you expand on that? Efficient in what way?

Efficient in the way of bringing the model to meet the criteria of autonomy faster. On one hand it may be something specifically efficient at reaching some autonomy qualities. OTOH it could be just something that efficiently uses the improvement in the model during training to make the subsequent training faster.

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