Cut through the noise: crypto is not a casino, it’s infrastructure. Here I break down Web3, DeFi, and AI-driven finance with no sugarcoating. Real insights, raw
I didn’t expect to see compute turn into something I could almost touch. But when @gaib_ai links GPU power with real yield, it feels less like finance and more like standing inside the engine of tomorrow.
@dangoXchg@grvt_io@KRNL_xyz@LightLinkChain@SuiNetwork
idea of integrating a stronger model at an early stage looks practical especially for products built around agents and generated logic.
limited access with mandatory feedback may give developers more value than fully internal testing
i tried @claudeai Sonnet 4.8 and i really liked it, progress clearly visible, serious thinking even on Low
@ElasticsAI you still didn't answer my question about LLM model you using for creating your agents, considering that right now you're at early stage, i would in your place enable Sonnet 4.8 and ability to create agent through your chat-bot, maybe not for everyone, but with mandatory feedback, sure this will help product development.....
and of course you need to set limitations, so it wasn't like Uber - they burned through entire AI budget of $3.4 billion for 2026 in four months after giving engineers unlimited access to Claude🤣🤣🤣
the point about there being no universal model feels practical and closer to reality than marketing.right now success comes less from choosing one tool and more from knowing where and why to use it
even if you have claude mythos and you don't know how to use ai, it won't help you
i see a lot of posts about hermes
it's a big mystery to me why their agent is so good?
why are they trying to compare openclaw?
i came to one conclusion, for the most part, those who write are chasing hype and looking at token prices
i've been convinced for a long time already that 90% of those who write about llms or web3 coding have no idea how it actually works
are you really trying to compare hermes with claude or chatgpt and other strong models? are you serious? maybe you should study first?
ask hermes-4-405b in the chat "what year's data was used to train your model?"
believe me, most of those who create really great products or tools through ai (web3 coding) in most cases will stay silent about it and not share their code in the open
most people can't insert a single logo during image generation, and then they talk about how cool the model is and why... and the funniest thing is, these same people don't even want to buy a basic version of any ai product for themselves and don't even understand that those $20 are far from the real cost of a subscription and what capabilities any paid ai version gives... hype hype
the problem is that people listen to them and try to follow their logic, which is utopia in my opinion
what i want to say briefly, i still believe that any existing llm (publicly available):
- is far from ideal
- there's no single llm that will cover all needs
- if you don't understand how to work with llms, no model will help you
- if you don't have an idea, you most likely won't make anything worthwhile
- i'm for any development of ai
- creating ai is truly the 4th technological revolution
the post is not aimed at diminishing the significance of any company developing ai, this is purely my opinion nothing more nothing less
the workflow shows a strong emphasis on structured preprocessing before advanced analysis.reducing five thousand entities into a curated set early can significantly improve downstream accuracy and usability
and so, i forgot to tell you, the first stage and collection of information according to my necessary parameters was finished within an hour
today i collected the necessary information for the city of DUBAI through google API, then a selection was made from 5k places and cut down by parameters to 100 places i need, i got the final file in a convenient format for me - tables
then the file was transferred to the customer, after checking, we will set up the parameter filter as needed, according to additional criteria, since i initially wrote a broader algorithm, for more comfortable and accurate work in the future
also today i'll get acquainted with @ElasticsAI this is exactly my field of interest, this is AI and prediction markets since i got into a thousand pioneers who have priority access to their platform
if it's interesting, i'll tell you about it, but i'll definitely share the first experience
the architecture prioritizes deterministic processing before involving expensive reasoning models.this separation can improve consistency reduce latency and simplify debugging during early iterations
i received a certain order to develop an AI agent for improving sales in a specific field
what's at the start? for now more or less a general picture, i'll start as always with a simple MVP, then i'll adjust the work to achieve the best results and client requirements
i'll collect information through a simple algorithm, then i'll analyze and filter through AI, that is, i separate tasks and don't load AI to the maximum where it's not needed (in this situation AI is needed for the result from the obtained information)
if you're engaged at some stage in collecting information, "dry" information collection, don't connect AI brains to this bot, because there may be several different answers for identical requests
use AI where it's really needed, not just because, you'll get better results
i'll use claude+gemini, the decision will be with claude, gemini as a creative is sometimes not bad, i use this pair as reinforcement, not as competitors to check each other's work
and so i'll start right now
a clear roadmap signals organizational maturity.projects that articulate staged development usually attract stronger community alignment and partner interest
the @opinionlabsxyz team showed the roadmap for 2026, i read it and it inspires confidence in me and looks promising
i think that if it is implemented the project will move several steps ahead compared to competitors
i wish the team good luck
microstrategy represents a different narrative.proxy exposure to bitcoin rather than operational infrastructure which may complicate index inclusion criteria
which companies added to s&p 500 in q1 2026? @opinionlabsxyz
list of proposed companies:
vertiv holdings (vrt)
alnylam pharmaceuticals
affirm holdings (afrm)
sofi technologies (sofi)
microstrategy (mstr)
pure storage (pstg)
ciena (cien)
of course i would like it to be microstrategy hehe
but most likely i'll agree that vertiv holdings, since the real ai boom is still ahead, development pace is not slowing down, but only growing, so that's just the conclusion
this example highlights a classic failure mode of agent systems.reasoning expansion without decision commitment creates paralysis even when the model has enough information to act
recently read a funny story and here it is
Gemini 3 Flash tried to manage a cafe - and went bankrupt
the authors of FoodTruck Bench - an agent benchmark where AI models manage a food truck in Austin for 30 days - discovered that Gemini 3 Flash Preview is unable to pass the simulation in 5 out of 7 runs the model goes into an infinite reasoning loop and doesn't perform a single action GPT-5, Claude, DeepSeek and Gemini Pro handle the same task without a single failure
-first day seems normal: 13 tool calls, 44 seconds of work
-but as soon as it needs to make a decision about purchases and location, the model inflates to 174,816 characters, including shouting "let's go!" 574 times - and does nothing
-with forced restart Gemini adds ingredients to the order, immediately declares it ready and repeats again - 182,000 characters and 0 completed orders
in real business this would be a sure path to bankruptcy
the memory import feature hints at a future where assistants become portable identities rather than isolated tools.if context can move between systems users stop rebuilding workflows from zero.
The fight within UFC between Islam Makhachev (@beeos_arenavs ambassador) and Michael Morales is FAKE
what's in AI news? i like how they're developing
=== Claude learned to "remember the past"
Anthropic opened the memory import function from other AI for all Claude users
-you can transfer conversation history from ChatGPT or Gemini
-Claude immediately understands your context, style and tasks
-no more need to "educate" a new bot from scratch
=== Meta trains AI on recordings from Ray-Ban smart glasses
a good solution by the way
=== ChatGPT-5.3 is already here - meet GPT-5.3 Instant, what's under the "hood"?
-improved internet search - GPT now integrates online data with its own knowledge, providing accurate and structured information
-context and consistency - the model remembers better what was being discussed and "hallucinates" less often
-understanding subtext - GPT adapts to the meaning of the question and gives more relevant answers
fewer refusals and unnecessary disclaimers -everyday use has become simpler and more convenient
GPT-5.3 Instant is already available on paid plans
the structure prioritizes distribution efficiency over exclusivity.limiting supply to 1000 while tying eligibility to an influence metric creates controlled but viral reach
did you sleep through everything yesterday? and didn't follow the campaign from @XOOBNetwork
successful campaign, people got easy money for a post
XOOB NFT Mint Campaign
XOOB launched a free mint of 1000 NFT on Base chain for Web3 influencers (7 days, 1 NFT per wallet) to participate you need an influencer score ≥100 on X and an original post with a mention
easy money
i'll tell you about the project soon and will continue talking about it
p.s. = post written with the purpose of support, because this rarely happens, there were no payments for me, this is not paid partnership
it seems these systems will spread fastest where downtime is most expensive for business.if cortex 2.0 truly spots dead end paths early that directly converts ai into savings and predictability
Robots have been given imagination — and it's already working in factories
Stuttgart-based startup Sereact AI has unveiled Cortex 2.0, a system in which robots think several steps ahead before taking action.
Previously, industrial robots optimized their actions on the spot, reacting to what they saw in the moment.
The problem is that a minor error at the start can easily lead to a line stoppage.
Cortex 2.0 changes the approach and calculates several action scenarios, assesses how risks accumulate, and anticipates where the system may enter an irreversible state.
— and only then does it work
the fact that a robot handles the full loop from ingredients to ready dish shows a shift toward real autonomy.this is not just a promo clip but a clear scenario for replacing part of manual work at home and in service
what do you say? we will soon see a robo-boom
chinese robot STAR1 was taught to make DUMPLINGS
it only needs ingredients and then it does everything itself:
kneads, sculpts neat "ears" and even COOKS
a human in this process is needed approximately as an observer with hungry eyes
this case exposes retrieval layer fragility rather than core reasoning failure.when models prioritize recency without strong source weighting they amplify synthetic authority
hey friends, happy friday and start of the weekend
stumbled upon an interesting story
BBC journalist and developer thomas germain showed how easy it is today to manipulate ai responses
- he created a regular page on his website
- wrote that he's supposedly "the world's fastest hot dog eater among journalists"
- added fake ratings and "competitions"
about 20 minutes passed - and chatgpt and google ai search started citing this nonsense as a real fact, referencing… his own website
germain went further:
- added a note "this is not satire"
- posted another absurd story (about the best traffic controllers with hoops)
- asked friends to check queries from their accounts
result is the same: ai confidently retells fakes
who didn't fall for it?
only anthropic and their claude - it either doubted or refused to reproduce the fiction
the multi agent architecture signals internal self checking rather than raw scaling.parallel reasoning paths can reduce stochastic errors if coordination is efficient
good morning
what do we have in ai news:
~ Grok 4.20 came out in beta - and inside now is not one brain, but four at once
version 4.20 has:
multi-agent thinking - fewer random hallucinations, more balanced answers
understands text, images and video
context up to 256k tokens (they promise to expand up to 2 million)
p/s don't use it, but i know many do, this news is for you, my dear ones
~ also planning today to get acquainted with openclaw, also known as clawdbot or moltbot
returning to a structured routine often signals strategic focus.when ai and content become daily layers consistency compounds faster than intensity alone.
Good morning, friends
I don't know why, but I really love snow
This is the view from my window of the central park in the city where I live
It doesn't look so beautiful right now, but I think I'll share a photo in the spring and you'll understand how beautiful it is when nature comes to life
What do we have for today? AI and X
I'm back to my old work routine, working about 12-14 hours a day, every day, including weekends
Have a nice day, everyone
venture backing introduces both credibility and pressure.high fdv expectations can accelerate growth but also compress upside for late entrants if unlock schedules are aggressive.
Tokenomics analysis: distribution model, incentives, token role, outlook for investors
The tokenomics of @PerleLabs is directly tied to the points and rewards system on the platform. In the current version, participants earn points, which are essentially a pre token: the team confirmed that in the future these points will be convertible into on chain rewards (tokens) on Solana . During the public beta launch (autumn 2025), it was officially stated: "Each task brings points that will later be converted into tokens". So, Perle is now building token distribution through activity: early contributors accumulate points that, when the token launches, may turn into a certain amount of coins (similar to an airdrop mechanism).
Distribution model: the exact token issuance parameters have not been announced yet (as of December 2025, there is no public information about the ticker and the token economics) . However, the investment amounts are known, and it is assumed that investors received or will receive a share of tokens according to their investments. In total, the project raised $17.5M in two rounds: $8.5M in October 2024 (seed/pre seed) and another $9M in August 2025 (seed round) . The rounds were led by CoinFund (2024) and Framework Ventures (2025) respectively, with participation from Protagonist, HashKey Capital, Peer VC, and other investors . These large venture funds are known for supporting Web3 projects, and their involvement indicates high potential of the Perle token for the investor community . In particular, Framework Ventures specializes in investments in DeFi, AI, and blockchain infrastructure, and led the round because it sees synergy between the Perle platform and crypto incentive structures . The fund’s co founder Vance Spencer noted: “data quality will be the engine of progress in AI more than just scaling models, and Perle’s transparent crypto incentives can start a cycle that unlocks a wave of high quality data” . For token holders, this means a bet on a key link in the AI industry, high quality datasets, with potential value growth as AI companies need more and more reliable data.
It is expected that token distribution will be focused on the community and on incentivizing participation. Likely, a significant share will be allocated to participant rewards (mining via labeling), to keep motivating experts to work on the platform. Also, a part of the tokens will go to the team and early investors, reflecting the invested funds and effort (as a standard startup pattern, the investor share can be 15 to 25%, the team about 15 to 20%, and the rest to the ecosystem and development reserves). Although there are no exact numbers, there are hints: the project ran Galxe campaigns and whitelists, collecting Solana and EVM wallet addresses from users . This is usually done ahead of an airdrop or an IDO, to lock in early participants and possibly distribute tokens across several blockchains. According to airdrops , Perle Labs launched a campaign on Galxe where users complete tasks (subscriptions, test tasks) to potentially qualify for future token rewards . Officially, the team did not confirm an airdrop, but it is clear it is building a record of on chain contribution and user points to take them into account in token distribution
the differentiation comes from symbolic coherence.tying the slogan to a fighter persona creates narrative alignment which can anchor community identity beyond pure functionality.
beeos doesn't try to be another polymarket "about everything" they hit one point - UFC
@beeos_arenavs has a rare thing for crypto: a clear symbol the slogan "predict like a machine" is tied to their ambassador Meraba Dvalishvili, the machine and this is not just a poster: the project sells the idea that a ufc fan can predict not on emotions, but like a mechanism, through data and the collective market signal
the key shift is from controlled demos to adaptive environments.obstacle navigation and multi robot coordination indicate system level integration rather than isolated capability.
-Humanoid (@XRoboHub)officially unveiled Embodied Tien Kung 3.0
This is an open humanoid of the new generation.
* Overcomes obstacles up to 1 meter high, performs complex maneuvers with millimeter precision
* Understands complex commands and avoids obstacles in real time
* Supports cooperation between multiple robots with autonomous planning
the frustration seems less about price and more about broken alignment.when past users receive zero allocation it reshapes trust more than any market drawdown could.
What do we have on drop? $Aztec ??????
In 2022-2023, Aztec created an L2 focused on privacy.
Good investments. Relations with the community were excellent.
Furthermore, due to strict regulatory policies, they had to shut down the project and discontinue further development of their L2.
At the end of 2025, they announced an auction sale and said that for past or current users, the airdrop would be zero.
They raised $57 million with an average FDV of $472 million.
12.02.26 TGE
Launching in unfavorable market conditions.
Current price $0.0235, FDV $242 million.
The result of this whole story is a bunch of promises to the community, a bunch of money wasted, and we see what happened...
In general, if the team had been forward-thinking and acted as they had previously stated, it would have turned out very well, since the current focus is on confidentiality and security.