AI such as ChatGPT or siri cannot read between lines or understand non-verbal languages such as eye contact, body language, social distance , touch , voice (paralanguage), physical environments/appearance, and use of objects. In addition, it cannot tell or guess the cultural ,social or academic background and have a conversation according to the back grounds. Making it happen will take a long time. So now, let’s focus on maintaining consistency in conversation in AI. In order to keep a conversation going back and forth with consistency the need for Working memory like components is crucial. Does current AI have enough conversational capability?

1. Does AI need a Working Memory?

3. Working memory is
what is happening right now
and it lasts around 10-15sec to
maximum
about 30 seconds

4. Working memory is
So if I tell you my phone
number, and before you can get
it into your cellphone
or write it down,

5. Working memory is
You gonna repeat 555-1234,
555-1234…

6. Working memory is
So as long as you repeat it, it's
in your !

7. Working memory is
but when you stop repeating it,
it leaves your .

8. Working memory is
So is
.

9. or Working memory is
a remarkable ability to
Neuroscience-Inspired Artificial Intelligence (2017)

10. or Working memory is
together are referred to as working memory.
is composed of concepts that
are
ARTIFICIAL INTELLIGENCE SOFTWARE STRUCTURED TO SIMULATE
HUMAN WORKING MEMORY, MENTAL IMAGERY, AND
MENTAL CONTINUITY(2022)

11. or Working memory is
“Short-term or “ is likely
composed of many different processes—from
very simple ones where you need to recall
something you saw a few seconds ago, to
more complex processes where you have to
manipulate the information you are holding in
memory,” said David Freedman, professor of
neurobiology (2019)

12. the academic or athletic
underachievement

13.  You cannot pay attention during class and schoolwork.
 You cannot solve complex math problems.
 You have difficulty with reading comprehension.
 You cannot give a good performance in sports.
 These are common symptoms of students with LD or ADHD.

16. For example,ChatGPT, developed by OpenAI,
is a language model. It excels at understanding
and generating human-like text based on
patterns and relationships in the vast amount of
data it has been trained on. Unlike Siri,
ChatGPT engages in conversations rather than
executing specific tasks

17. How about Ai? Does Ai need to improve or
expand a Working memory like capacity?
But ChatGPT cannot read between lines or
understand non-verbal languages such as eye
contact, body language, social distance , touch ,
voice (paralanguage), physical
environments/appearance, and use of objects. In
addition, it cannot tell or guess the cultural ,social
or academic background and have a conversation
according to the back grounds.

18. How about Ai? Does Ai need to improve or
expand a Working memory like capacity?
But ChatGPT cannot read between lines or understand
non-verbal languages such as eye contact, body language,
social distance , touch , voice (paralanguage), physical
environments/appearance, and use of objects. In addition, it
cannot tell or guess the cultural ,social or academic
background and have a conversation according to the back
grounds.

19. In order to keep a
going back and forth
with consistency
the need for like
components is crucial.

20. Computer and Human Short-term Memory
Hierarchy
Artificial Intelligence Software Structured to Simulate Human Working Memory,
Mental Imagery, and Mental Continuity (Reser, Jared Edward 2022/03/29)

21. Artificial Intelligence vs Human Intelligence (2023)

22. Artificial Intelligence vs Human Intelligence (2023)

23. Artificial Intelligence vs Human Intelligence (2023)

24. Artificial Intelligence vs Human Intelligence (2023)

25. Artificial Intelligence vs Human Intelligence (2023)

26. The latest machine-learning systems are brilliant at
certain tasks, like recognizing faces in images or
spoken words. And with practice they can learn to
perform complex tasks like playing computer
games to an expert level. But they require huge
quantities of specific data for training, and
much of what they have
learned in memory for use later.
What Happens When You Give an AI a Working Memory?(2016)

27. suffer from
. Unlike humans, when
these networks are trained on something new,
they what was learned before.
Brain-inspired replay for continual learning with artificial neural networks
Gido M. van de Ven, Hava T. Siegelmann & Andreas S. Tolias
Nature Communications volume 11, Article number: 4069 (2020)

28. Current state-of-the-art
can be trained to impressive performance on
a wide variety of tasks. But when these
networks are trained on a new task,
previously learned tasks are typically
.
Brain-inspired replay for continual learning with artificial neural networks
Gido M. van de Ven, Hava T. Siegelmann & Andreas S. Tolias
Nature Communications volume 11, Article number: 4069 (2020)

29. One solution would be
to store previously encountered examples and revisit them
when learning something new.
in the brain—which clearly has implemented an efficient and
scalable algorithm for continual learning—the reactivation of
neuronal activity patterns that represent previous experiences
is believed to be important for stabilizing new memories. Such
memory replay is orchestrated by the hippocampus but also
observed in the cortex, and mainly occurs in sharp-
wave/ripples during both sleep and awake.
Brain-inspired replay for continual learning with artificial neural networks. Nat
Commun 11, 4069 (van de Ven, G.M., Siegelmann, H.T. & Tolias, A.S. 2020)

30. Another solution would be
,
which subsequently achieved state of the art
performance across a variety of domains.
LTSMs allow information to be gated into
a fixed activity state and maintained until an
appropriate output is required
Neuroscience-Inspired Artificial Intelligence(Demis Hassabis, Dharshan Kumaran , Christopher
Summerfield , Matthew Botvinick 2017)

31. This externalization allows the network controller to
learn from scratch (i.e., via end-to-end optimization)
to perform a wide range of complex memory and
reasoning task
Neuroscience-Inspired Artificial Intelligence(Demis Hassabis, Dharshan
Kumaran , Christopher Summerfield , Matthew Botvinick 2017)

32. Yes, AI needs a Working Memory
Externalization ⇒
Internalization