On Tue, Jan 7, 2025 at 3:46 AM Abu Naser <[email protected]> wrote:
>
> I am interested in applying agi in genomics. Is there any tutorial on how to
> build models, etc. ?
OpenCog is not AGI, since that doesn't exist. Although everyone says
they are working on it. OpenCog is a system for implementing various
aspects of AGI: exploring, experimenting, tinkering.
OpenCog has a set of components, ranging from rock-solid, stable,
high-performance, to buggy, incomplete, abandoned.
At the stable end is the AtomSpace, which is a way for storing
anything in any way: vectors, dense networks, sparse networks, graphs,
things that flow or change in time, whatever. It has been used for
storing genomic and proteomic data, and the reactomes connecting them.
I did look at that code: the core storage idea seemed fine. Some of
the processing algorithms were poorly designed. I was called in for
emergency repairs on one: after a month's worth of work, I got it to
run 200x faster. That's right, two-hundred times. Unfortunately, by
then, the client lost interest. The moral of the story is that
software engineering matters: just cause its whiz-bang AI doesn't mean
you can ignore basic design principles. So it goes.
That project was mining for small reactome networks: for example,
given one gene and one protein, find one other gene, two up/down
regulators, and one other (I don't know, I'm not a geneticist) that
formed a loop, or a star-shape, or something. The issue was that these
sometimes could be found in a second or two, and sometimes it would
take an hour of data-mining, which was annoying for the geneticists
who just wanted the answer but didn't want to wait an hour. Of course,
as the reaction network moved from 4 or 5 interactions, to 6 or 8,
there was a combinatorial explosion.
The reason for this was that that system performed an exhaustive
search: it literally tried every possible combination, so that even
obscure, opaque and thus "novel" combinations would be found. The
deep-learning neural nets provide an alternative to exhaustive search.
However, no one has hooked up a deep learning net for genomics into
opencog, so you will not get lucky, there.
MOSES (that you had trouble building) is a system for discovering
pattern correlations in datasets. One project applied it to find a
list of about 100 or 200 genes that correlated with long lifespans.
The code, the adapter that did that was either proprietary, or was
lost to the sands of time.
I've been working on a tool for pattern discovery. In principle ("in
theory") it could be used for genomics data. In practice, this would
require adapters, shims and rejiggering.
And so what? You use it, you can find some patterns, some
correlations, and so what? There must be a zillion patterns and
correlations in genomic data, so you have to be more focused than
that.
Some parts of the AI world talk about building "virtual scientists"
that can "create hypotheses and test them". OpenCog does not do this.
Creating an AI scientist that automatically makes discoveries sounds
really cool! An exciting and new shiny future of AI machine
scientists! But for one thing: the mathematicians have already tried
this.
Math is crisp enough that it is very easy to "create hypotheses and
test them". They're called "theorems",
and you test them with "theorem provers". Turns out that 99.999% of
all theorems are boring (to humans). Yes, it might be true that X+Y=Z,
but who cares? So what?
I suspect a similar problem applies to genomics. Yes, someday, we
might have AI scientists making "profound" discoveries, but the "so
what?" question lingers. Unless that discovery is very specific: "take
these pills, eat these foods and exercise regularly, you will become
smarter and have a longer healthspan", that discovery is useless, in
and of itself.
There is a way out. In science, it turns out that making discoveries
is hard, but once you have them, you can remember them, so you don't
have to re-discover from scratch. You write them down in textbooks,
teach the next generation, who then takes those discoveries and
recombines them to make new discoveries. In mathematics, these are
called "oracles": you have a question, the oracle can answer them
instantly. Now, you can't actually build the pure mathematical
definition of an oracle, but if you pretend you can, you can make
deductions that are otherwise hard.
If you can collect all the hard-to-find interrelations in genetics, so
that the next time around it's instant and easy, then .. ?
Let amble down that path. The various LLM's -- ChatGPT, and the OpenAI
stuff and the Gemini from google are question-oracle-like things. You
can ask questions, and get answers. OpenCog does NOT have one of
these, and certainly not one optimized for genomics questions. If
you want a natural language, chatbot interface to your genomics
oracle, OpenCog is not the thing. Because OpenCog does not have
chatbot natural language interfaces to its tools: the tools are all
old-style, "Dr. DOS Prompt", and not windows-n-mouse interfaces, and
certainly not LLM chatbots. Alas.
Could you hook up an LLM-based chatbot to a large dataset of genomics
data (using, for example, the OpenCog AtomSpace to hold it, and
various tools to data-mine it?) I guess you could. But no one has done
this, and this would be a large project. Not something you'd
accomplish in a week or two of tinkering.
-- linas
>
> Kind regards,
>
> Abu
>
>
>
> On Tue, 7 Jan 2025 at 03:55, Linas Vepstas <[email protected]> wrote:
>>
>> Hi Abu,
>>
>> I just merged a fix into as-moses which I think will solve the build
>> problem you had. Try `git pull` on as-moses and with luck, the problem
>> will be gone.
>>
>> --linas
>>
>> On Mon, Jan 6, 2025 at 5:56 PM Linas Vepstas <[email protected]> wrote:
>> >
>> > I can't reproduce this problem, so I will need your help. Try changing
>> > bind to std::bind and changing _2 to std::placeholders::_2
>> >
>> > If that doesn't fix it, try try changing the two std's to boost, so,
>> > boost::bind and boost::placeholders
>> >
>> > Boost has been the source of ongoing breakage, and the decision to use
>> > it was a mistake. So it goes.
>> >
>> > --linas
>> >
>> > On Mon, Jan 6, 2025 at 3:49 PM Abu Naser <[email protected]> wrote:
>> > >
>> > > Hi Linas,
>> > >
>> > > I have another error while I was installing asmoses:
>> > > /asmoses/opencog/asmoses/reduct/reduct/flat_normal_form.cc:34:36: error:
>> > > call of overloaded ‘bind(std::negate<int>, const boost::arg<2>&)’ is
>> > > ambiguous
>> > > 34 | bind(std::negate<int>(), _2))) != c.end());
>> > >
>> > > Please let me know if you have any solution for this issue.
>> > >
>> > > Kind regards,
>> > > Abu
>> > >
>> > > On Mon, 6 Jan 2025 at 20:06, Abu Naser <[email protected]> wrote:
>> > >>
>> > >> Thank you Linas. It works now.
>> > >>
>> > >> Kind regards,
>> > >>
>> > >> Abu
>> > >>
>> > >> On Mon, 6 Jan 2025 at 19:41, Linas Vepstas <[email protected]>
>> > >> wrote:
>> > >>>
>> > >>> Hi Abu,
>> > >>>
>> > >>> class concurrent_set is provided by cogutils -- the solution would be
>> > >>> to got to
>> > >>> cd cogutils, git pull, rebuild and reinstall. Then the atomspace
>> > >>> should build. See here:
>> > >>>
>> > >>> https://github.com/opencog/cogutil/blob/be54bfcadaf8439f324cf525781b254c87fa0722/opencog/util/concurrent_set.h#L162-L168
>> > >>>
>> > >>> --linas
>> > >>>
>> > >>> On Sat, Jan 4, 2025 at 6:11 AM Abu Naser <[email protected]> wrote:
>> > >>> >
>> > >>> > Hi Everyone,
>> > >>> >
>> > >>> > The following error is thrown while I was compiling atomspace on
>> > >>> > Ubuntu:
>> > >>> >
>> > >>> > opencog_repos/atomspace/opencog/persist/proxy/WriteBufferProxy.cc:85:14:
>> > >>> > error: ‘class concurrent_set<opencog::Handle>’ has no member named
>> > >>> > ‘clear’
>> > >>> > 85 | _atom_queue.clear();
>> > >>> >
>> > >>> >
>> > >>> > Is there any solution for this error?
>> > >>> >
>> > >>> >
>> > >>> > Kind regards,
>> > >>> >
>> > >>> > Abu
>> > >>> >
>> > >>> > --
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>> > >>>
>> > >>>
>> > >>>
>> > >>> --
>> > >>> Patrick: Are they laughing at us?
>> > >>> Sponge Bob: No, Patrick, they are laughing next to us.
>> > >>>
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>> >
>> >
>> >
>> > --
>> > Patrick: Are they laughing at us?
>> > Sponge Bob: No, Patrick, they are laughing next to us.
>>
>>
>>
>> --
>> Patrick: Are they laughing at us?
>> Sponge Bob: No, Patrick, they are laughing next to us.
>>
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--
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