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Re: Group Morons and the American Dream (Was: Corr.: now -> new)

From Mild Shock <janburse@fastmail.fm>
Newsgroups sci.physics
Subject Re: Group Morons and the American Dream (Was: Corr.: now -> new)
Date 2025-02-04 23:51 +0100
Message-ID <vnu5lo$vb6h$1@solani.org> (permalink)
References <vn98q6$ie21$4@solani.org> <vnslb8$ue77$4@solani.org> <vnu020$v7ev$2@solani.org> <vnu4f7$vahi$1@solani.org> <vnu4k7$vahi$2@solani.org>

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Hi

For DeepSeekMath I imagine the group concept:

 > - Hindu
 > - Jewish
 > - Liberal
 > - Asian

Transfers to groups such as:

- Calculus
- Group Theory
- Number Theory
- Probability Theory

Got it?

Mild Shock schrieb:
> Hi,
> 
> The biggest group morons are those that
> dream that they can profit by relocating
> from their own group of people,
> 
> to a group of american people, and then
> cry when their assets get frozen or who
> knows what happens. The papers I posted
> 
> are about automatically tuning into groups:
> 
>  > Group Preference Optimization
>  > https://arxiv.org/abs/2310.11523
>  >
>  > DeepSeekMath: Pushing the Limits
>  > https://arxiv.org/abs/2402.03300
> 
> Its actually quite amazing how machine
> learning can utilize group identification
> to customize how a conversational software
> 
> agent interacts. Currently I think is a
> variant of fine tuning, but on a different
> model level that is called policy. The first
> 
> paper has a figure with the following groups:
> 
> - Hindu
> - Jewish
> - Liberal
> - Asian
> 
> Have Fun!
> 
> Bye
> 
> Mild Shock schrieb:
>> Hi,
>>
>> Typo: now -> new
>>
>>  > to generate now thinking
>>
>> Should read:
>>
>>  > to generate new thinking
>>
>> I shit and piss on some asslicking group
>> that cannot think on his own. Thank god
>> USENET has only rarely such group morons.
>>
>> Bye
>>
>> Mild Shock schrieb:
>>> Hi,
>>>
>>> You wouldn't notic that I speak for myself
>>> always and ever. Just remove the links and
>>> you see its all text original by me.
>>>
>>> I always post geniun commentary to current
>>> events which are solely the product of my
>>> own mind. I do not intend to educate something.
>>>
>>> My intention is to document my current
>>> understanding and to generate now thinking.
>>> If you have expected some schooling, I am very
>>>
>>> sorry for you. I never post boring schooling.
>>>
>>> Bye
>>>
>>> ---------------- cut here -----------------
>>>
>>> Because of the wide availability of Machine Learning
>>> via Python libraries , the whole world (at least China)
>>> has become a big Petri Dish that is experimenting with
>>>
>>> new strategies to evolve brains on the computer.
>>> Recent discovery seems to be Group Preference Optimization.
>>> This is when you make the chat bot, detect and react
>>>
>>> differently to different groups of people. It seems to
>>> work on the "policy level". I don't understand it yet
>>> completely. But chat bots can then evolve and use
>>>
>>> multiple policies automatically:
>>>
>>> Now it seems that it is also at the core of DeepSeekMath,
>>> what is possibly detected is not group of people, but
>>> mathematical topics, so that in the end it excells.
>>>
>>> When unsupervised learning is used groups or math
>>> topics might be found from data, through a form of
>>> abduction.
>>>
>>> ---------------- cut here -----------------
>>>
>>>
>>> Physfitfreak schrieb:
>>>> On 2/4/25 3:06 AM, Mild Shock wrote:
>>>>> Hi,
>>>>>
>>>>> Because of the wide availability of Machine Learning
>>>>> via Python libraries , the whole world (at least China)
>>>>> has become a big Petri Dish that is experimenting with
>>>>>
>>>>> new strategies to evolve brains on the computer.
>>>>> Recent discovery seems to be Group Preference Optimization.
>>>>> This is when you make the chat bot, detect and react
>>>>>
>>>>> differently to different groups of people. It seems to
>>>>> work on the "policy level". I don't understand it yet
>>>>> completely. But chat bots can then evolve and use
>>>>>
>>>>> multiple policies automatically:
>>>>>
>>>>> Group Preference Optimization
>>>>> https://arxiv.org/abs/2310.11523
>>>>>
>>>>> DeepSeekMath: Pushing the Limits
>>>>> https://arxiv.org/abs/2402.03300
>>>>>
>>>>> Now it seems that it is also at the core of DeepSeekMath,
>>>>> what is possibly detected is not group of people, but
>>>>> mathematical topics, so that in the end it excells.
>>>>>
>>>>> When unsupervised learning is used groups or math
>>>>> topics might be found from data, through a form of
>>>>> abduction.
>>>>>
>>>>> Bye
>>>>>
>>>>> Mild Shock schrieb:
>>>>>> Hi,
>>>>>>
>>>>>> Wait till USA figures out there is a second
>>>>>> competitor besides DeepSeek, its called Yi-Lightning:
>>>>>>
>>>>>> Yi-Lightning Technical Report
>>>>>> https://arxiv.org/abs/2412.01253
>>>>>>
>>>>>> It was already discussed 2 months ago:
>>>>>>
>>>>>> Eric Schmidt DROPS BOMBSHELL: China DOMINATES AI!
>>>>>> https://www.youtube.com/watch?v=ddWuEUjo4u4
>>>>>>
>>>>>> Bye
>>>>>>
>>>>>
>>>>
>>>>
>>>> Throwing papers at us (i.e. in usenet) although better than nothing, 
>>>> it still is an extremely inefficient way to communicate.
>>>>
>>>> Speak, yourself, in the way that a first year undergraduate prof 
>>>> explains stuff to the students who just a few months earlier 
>>>> finished their high schooling.
>>>>
>>>> Then you will communicate.
>>>>
>>>> If it is too difficult to do that (cause requires deep understanding 
>>>> of the subject by yourself), or, if you don't get time doing all 
>>>> that, then break the job down into little pieces. A day at a time, 
>>>> or a week at a time.
>>>>
>>>> You'd be spending the same amount of time as you are now, and yet 
>>>> you will actually communicate something with those with physics 
>>>> background.
>>>>
>>>> Did I have to say this? I don't think so. But your intentions here 
>>>> are vague. But if you need support for your own gains in 
>>>> understanding the subject, you just have to do it the way I 
>>>> explained above. Then you will get that support. Not from Bozos and 
>>>> "engineers", but from me and anybody with actual physics background 
>>>> and such trainings.
>>>>
>>>> There are a few actual physicists in relativity group that can join 
>>>> in, but only if you do it the way I explained above.
>>
>

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