@thegeagroup is presenting the complete range of its #KOBseries, a new cost-efficient line of homogenizers reaching up to 400 bar. The series is designed to give small and medium production plants access to industrial-grade performance at an attractive... foodtechbiz.com/processing/g…

I would occasionally amaze people at my dairy job by coming in at a full fat man run from the parking lot, finding one of the production supervisors and telling him "Go tell the idiot you've got running the homogenizers that he's got foam in the level tank and he's cavitating He breaks my machine, I'm hanging him off a silo." Could tell by the change in pitch and rhythm - ventilation system carried it to the lot.

You can have one if you're willing to pay. There are industrial homogenizers. We had to get one for the lab but it was pretty huge... And $250k.. but the engineer from Germany will come over and teach the techs how to use it. 😂

TIPCO ENGINEERING SME IPO CLOSING TODAY. BRIEF REVIEW. AVOIDED NOW though the asking valuation is only 11x. Will consider later. Company is a capital equipment maker supplying bead mills, dispersers & homogenizers to chemical, paints, printing, packaging and other industries. Has order book of Rs.76Cr as of 31. Dec 2025. The product demand depends on expansion of Indian Industrial production. The products are good and import substitutes. Unlike recently listed Admach (Steel Industry dependent), TIPCO has lower risk since it caters to multiple industry segments.👍 In some ways (not exact at all), BEW Engineering is a peer (They don’t make exactly same machiones but equipments for local industries) . BEW has ~150Cr sales, 13% op margin and is valued at only 8x at Rs.78. Tipco reported Rs.130Cr in Fy25 at around 18% op margin. Rs.89 is at 11x its TTM earnings, on post IPO equity basis. Not expecting this stock to take off, due to basic focus only on 3 types of machinery for paint, chemical and packaging/printing industries. Looks reasonably good and stable. Would consider for investment, later. Feel no need for rush in this market. Suggest to assess by yourself and take your own decision, after further study, considering various factors discussed and any other info available.

Computer Scientists and Psychologists Warn: AI Is Flattening Human | ScienMag AI chatbots, powered by large language models (LLMs), are rapidly reshaping the ways in which humans communicate, think, and express ideas. While these advancements offer remarkable convenience and efficiency, a growing body of researchers warns of an unintended yet profound consequence: the homogenization of human expression. As billions of people increasingly rely on a limited number of AI systems for writing, reasoning, and problem-solving, there is mounting concern that this digital standardization may erode the cognitive diversity that underpins creativity and innovation. Zhivar Sourati, a computer scientist at the University of Southern California and lead author of a new commentary published in the esteemed journal Trends in Cognitive Sciences, explores this phenomenon in depth. Sourati cautions that the subtle uniformity introduced by widely adopted LLMs is not merely superficial but extends to how individuals conceptualize and reason about the world. “People are inherently diverse in how they approach language and thought,” Sourati explains. “When these individual styles are funneled through the same AI algorithms, we begin to see convergence in expressions, perspectives, and problem-solving strategies.” This convergence challenges the rich tapestry of human cognitive diversity that is essential to societal advancement. Historically, groups and cultures have thrived precisely because of their varied ways of thinking—offering unique solutions and novel ideas to complex challenges. However, the ubiquitous influence of LLM-based chatbots, heavily trained on datasets dominated by Western, educated, industrialized, rich, and democratic (WEIRD) populations, risks narrowing this diversity. The training data’s inherent skew leads LLMs to produce outputs that echo a limited slice of human experience and epistemology. More troublingly, the drive for polished, AI-assisted writing is gradually eroding individual voice and ownership over creative output. People using chatbots to refine text often find their distinctive linguistic fingerprints diluted, resulting in homogenized content that prioritizes statistical norms over personal flair. This can reduce users’ perceived creativity and diminish the motivational drive to generate original work. The broader implication is a reshaping of what is accepted as credible or authoritative language, altering social norms around communication and reasoning. Recent empirical studies reinforce these concerns by showing that LLM-generated outputs lack the variability characteristic of human writing. Moreover, experiments examining group creativity indicate that when collective ideation processes rely on AI intermediaries, the total number and novelty of ideas diminish compared to groups collaborating without AI mediation. This suggests that LLMs may be unintentionally suppressing the collaborative cognitive dynamics critical for breakthroughs and diverse problem-solving. Sourati further points to the social consequences of this homogenization. Even individuals who do not directly engage with AI tools feel indirect pressures to align their expression with the prevailing AI-mediated norms. This phenomenon can foster conformity, as people perceive AI-generated styles as socially acceptable or intellectually credible, making deviation seem less desirable or even inexplicable. Over time, this could solidify new conventional paradigms of thought and communication, potentially stifling dissent and innovation. Beyond linguistic effects, the influence of LLMs on reasoning styles is equally significant. Current models emphasize linear “chain-of-thought” reasoning, which entails explicit stepwise logic. While effective for certain tasks, this approach underrepresents other cognitive styles such as intuitive and abstract reasoning, which are sometimes better suited for complex or novel problem-solving. Such an emphasis on linearity risks narrowing the cognitive toolkit available to users, subtly guiding their mental processes and expectations toward a constrained reasoning framework. The gradual transfer of cognitive agency from users to models represents another critical concern. Users interacting with AI-generated suggestions frequently accept “good enough” continuations rather than actively crafting their own responses. This behavioral shift results in diminished intellectual engagement and adaptation, as the generative power of the model supersedes personal ideation. This transition marks a fundamental change in human-AI interaction dynamics, with profound implications for how future generations will think and create. Addressing these challenges requires deliberate actions from AI developers. The commentary advocates for incorporating authentic, global diversity into LLM training datasets—not merely random noise but a comprehensive representation of the vast cultural, linguistic, and cognitive plurality present in humanity. Such inclusiveness would foster models capable of supporting a wider array of reasoning styles, linguistic expressions, and perspectives, thereby preserving the cognitive heterogeneity vital for innovation and societal resilience. Sourati emphasizes that enhancing diversity in AI models must be paired with shifts in human interaction paradigms. Users should be encouraged to engage critically and creatively with AI outputs instead of passively adopting them. Educational initiatives and interface designs must promote active exploration, allowing human cognitive capacities to flourish alongside and in cooperation with AI technologies. Ultimately, reinforcing cognitive diversity through the thoughtful integration of heterogeneous data sources and user practices promises to enrich collective intelligence. Diverse AI systems can function not as homogenizers but as amplifiers of human potential, enabling societies to confront increasingly complex and multifaceted challenges with a broader spectrum of ideas and approaches. This vision of AI as a collaborator rather than a standardizer highlights the urgent need for conscious stewardship in AI development and deployment. The research underlines an urgent philosophical and practical crossroads: will AI technologies become agents of uniformity, compressing the vast spectrum of human expression into monolithic norms? Or will they serve as catalysts for expanding cognitive frontiers, amplifying the distinctiveness and creativity that define humanity’s past and future? The answer lies in recognizing and addressing the biases embedded in AI and reaffirming the fundamental role of diversity in intellectual and cultural evolution. In summary, as AI chatbots and LLMs become pervasive tools in everyday life, understanding and mitigating their homogenizing effects is paramount. The ongoing technological revolution must be accompanied by rigorous efforts to embed diverse linguistic, cultural, and reasoning traditions into AI systems. By doing so, we can safeguard the diversity of human thought and maintain the fertile ground upon which creativity, innovation, and societal progress depend. scienmag.com/computer-scient…

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premodern india was not doing “kitchen beauty hacks.” it was running empirical r&d with formulation engineering long before the language of “colloids” & “emulsions” existed. repeated washing is essentially a manual emulsification process. fat globules shear, water content increases, ph shifts, & the ghee transitions toward a quasi-cream with far smaller lipid particles. modern cosmetic chemistry does the same thing with homogenizers and stabilizers :)

And this is why such rituals should not be made public. The appropriators and homogenizers will swoop in like falcons. One deity with a different name and they will start calling it an avatar of their own supreme god.

This is becoming my favorite page on Twitter 😬 I used to work with shear plate homogenizers (blast a 30kpsi stream at a plate) and the plate was made of tungsten carbide. Stuff is insane.

iirc Varg makes America an exception to his blood and soil Ôðalism. The one wild mixing pot of economic exploitation. Oddly enough, the same thing the global-homogenizers want.

The homogenizers of education evoke such rage in me that I cannot even fight them effectively. Luckily, we have @tracewoodgrains. Read Trace's deeply researched article about the schools that once educated DC's brightest black kids--and how they were fucking destroyed. And why.

AI is extra special for homogenizers

I remember homo Mel come along I like what's this they should drop fresh milk off on our porch you leave a bottle there they put a fresh one every day everything was taken care of back in the day women just sat around did not to play cards all the time now they work you avoid milk I used to work on homogenizers high pressure they break up the fat particles so you absorb the fat better it's unhealthy when they imagine it destroys the enzymes you're idiots

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Homogenizers Dash

Turn Wrenches and completely overhaul a pair of Homogenizers! But I’d rather be out riding my motorcycle! 🥲

I read in the low-carb groups that someone's surgeon told her that gall stones were due to under-usage from low-fat dieting. If you do get it removed (why can't they just remove the stones? never understood that) then all is not lost. My landlady had hers removed and is 100% high-fat carnivore with absolutely no issues. She does eat a lot of eggs, which are full of fat homogenizers, kind of doing the same job. I believe heavy cream has this property also.

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