Anonymous member


Career development 6d
hello,
I am looking for project management associate internship or entry level opportunities. Be it remote or on site i am available. Any assistance grabted is highly appreciated.
Load more...

Alex Turig


Career development 2h

I know working with family can be a bad idea, so I told my sister right away that I wouldn’t hire my nephew in my department.
First, I know he’s careless. Second, I don’t want to keep letting him off for being late or skipping work just because my sister asks.
Now my parents are upset and won’t talk to me. It’s hard emotionally, but I don’t want to risk my job or business.
How can I explain to... them so they stop pressuring me?

 more

  • On The Rail Radio

    1h

    Something like this? -
    “I love our family deeply, and that’s exactly why I had to make this tough call. I’m not judging [nephew’s name] as a person,... but my department is my responsibility, and every employee affects the whole team. I’ve seen patterns that could hurt our work environment, and I need to treat every staff member the same—no favorites, no exceptions.
    I know this hurts, and I’m sorry it feels personal. I’m not turning away family—I’m protecting the professional space that supports me. I hope you can see it’s not about shutting anyone out. It’s about staying true to what I’ve built and the standards I’ve promised to keep.”
     more

    1

DOPE KID DRE ZAMBIA
Career development 2d

Hi, I am a beginner in graphic design, although I graduated as a graphic designer, I'm having a hard time finding a job. Could you provide me with some good advice?
3   

  • Eluk Chosen

    4h

    Dear all,I am currently looking for a job,I am an agricultural scientist. I hold a bachelor degree in agriculture and rural innovation.

  • Victor Ng'ani

    Pro
    4h

    Please clarify: what do you mean you are a beginner though you graduated in GD?

Load more...

Anonymous member


Career development 1d

Am finding difficulty in my current job, my close friend has been reporting false information about me and my boss has clashed with me upto the extent of giving me a warning letter. He is now taking things too personal but the Executive director doesn't support the idea of dismissing staff. What should i do friends
1   

  • Edward Okoth

    5h

    Stick to your values and remain you

  • Angela Harris

    10h

    Document everything. Send follow up emails to all parties after meetings and discussions summarizing what was discussed and agreed upon. This creates... a paper trail of facts. When raising your concerns to leadership and/or HR, speak about the facts and not the emotions. Most important, do not let what is happening to you impact your self esteem or confidence. And remember that coworkers are not your friends. Workplace is very competitive and some people only keep you close to control you. Stay calm, do your work and don’t let them see you sweat.  more

    1
Load more...

Career development

 7h

Back To Work BBQ helps hundreds enter the workforce


LEXINGTON, Ky. (WKYT) - Burgers, haircuts and job applications.

That's what's on the menu at the Jubilee Jobs Cookout on Friday.

"Our community is for people being well supported as they get into the workforce," says Jubilee Jobs CEO Mason King.

Jubilee Jobs connects over 40 employers with hundreds of people seeking their next career step.

On-the-spot job interviews, career services,... giveaways, and more are open to the public for free.

"Jubilee Jobs last year helped place over 600 people in employment at over 200 different employers all across Lexington. Today we have non-profit partners, we have manufacturing outfits, we have food service, all kinds of different opportunities," shared King.

Jubilee Jobs believes when you look good you feel good, and when you feel good you perform your best.

Free, on-site haircuts are offered to help people feel prepared.

"It can't be overstated, something as simple as getting clean clothes or a haircut, how it changes their entire level of confidence and translates to them being able to get good jobs," King explained.

King tells me these acts of care extend beyond haircuts and barbecues, helping support those before, during, and after they get a job.

"If you don't have a roof over your head, food in your belly, reliable child care, mental health services, you're not going to be successful getting a job let alone keeping one. That's why we have partners here today to help with that whole continuum of care to make sure people are well supported so they're set up to thrive when they get that 'you're hired!'" more

Career development

 7h

Best Resume Writing Services for IT Professionals and Freelancers - Twine Blog


Now, more and more websites make resumes specifically for freelancers and remote IT professionals. You'll find many skilled people fighting for the same jobs and contracts, so it's important that your resume looks good and is still relevant. This article includes some of the best resume services available today, what they give, where they fall short, and how much they cost.

Remote IT roles have... never been more competitive. Most companies now rely on Applicant Tracking Systems (ATS) to sift through countless resumes before a human sees them. These systems reject documents with incorrect keywords or formats that don't scan correctly. As a result, even qualified professionals can end up overlooked.

Specialized services step in to solve this problem. Instead of plugging details into a standard template, experienced writers build resumes designed to pass ATS checks and impress hiring managers. This approach is especially valuable for freelancers, developers, and cybersecurity experts, where showcasing results and project impact is significant. The table below highlights how professional resume services add value:

Several resume-writing companies have earned strong reputations for helping professionals in remote and technical fields present their skills clearly. Here's a closer look at those that consistently stand out:

CraftResumes combines direct collaboration with professional writers and quick delivery. Many customers value staying in touch with their assigned expert through the process. Services start around $139, covering ATS-friendly formatting and keyword focus. CraftResumes also offers LinkedIn profile updates and extra coaching for job interviews when needed. Turnaround can be as fast as 24 hours for urgent orders.

This service offers an extra layer of expertise. Resume writers at craftresumes.co take time to learn about past contracts, major achievements, and the specific technologies used. This process guarantees the final resume sounds genuine and tailored rather than generic. Another advantage is the time saved. Creating a polished, well-targeted resume requires hours of careful editing and keyword alignment. For freelancers, each day tweaking a CV is time that could go into building client relationships or exploring new projects.

ResumeWritingLab services online focus on personalized resumes for various industries, including tech and remote work. Their team offers resume and CV writing, LinkedIn profile optimization, and cover letter services. Prices usually begin at about $139, with turnaround times ranging from 3 to 5 business days. They also provide unlimited revisions within a set period to fine-tune details until the final draft feels right.

Recently introduced a feature called GetHiredNow, which includes help with job search strategy and application follow-up. Reports from the New York Post and The Sun suggest that this approach helps some candidates see faster responses from employers. TopResume also offers a 60-day guarantee, promising more interviews within that time frame. Prices vary based on the level of support.

Sometimes, combining full-service resume writing with self-guided editing tools works best. The Resume Writing Lab online services provide this middle ground. It allows professionals to get resume reviews, LinkedIn makeovers, review drafts, request changes, and stay more involved in shaping their documents. It's clear that these services have benefits, like knowing real tech job trends and making sure that applicant tracking tools can read well, but they cost more and take longer. For individuals skilled in technology or working from home, the investment can pay off by simplifying complicated experiences.

It is often recommended for people who want a quick turnaround. Its process includes scanning each resume through ATS software to catch missing keywords before sending the draft to clients. Basic services start around $159, while higher-tier plans include cover letters and additional editing rounds.

FindMyProfession has built a reputation for dependable work. Forbes has mentioned it among the better options for creating resumes that pass ATS checks without looking dull. Packages start at around $400 for a basic resume and cover letter and can reach higher amounts for executive-level services, which include LinkedIn profile updates.

Freelancers often need resumes that go beyond the traditional format. These documents must clearly and practically present short-term contracts, diverse project outcomes, and a wide skill set. Twine is a strong option for this need, offering access to writers with experience in HR or recruiting. Many specialize in resumes for consultants and independent professionals, with services typically starting at $35. Extras like LinkedIn profile updates or cover letter writing are also available. Fiverr offers a broader range of freelance-focused services, often at lower starting prices.

Some services work only with technical professionals, which can be a major advantage for IT roles or remote positions. They understand how to present skills that go beyond buzzwords. Besides RWL and CraftResumes, Find My Profession is known for helping IT candidates at different career stages. Prices start around $395 for junior resumes and rise to nearly $1,000 for executive packages. Turnaround usually takes about a week, though faster options are available. They also include a service where their team reaches out to employers on the client's behalf.

Quantum Tech Resumes focuses exclusively on tech jobs. Basic resume packages begin at $997, and full bundles with LinkedIn updates and coaching cost over $1,700. These projects often take two to four weeks, mainly because they involve in-depth interviews and multiple drafts. iCareerSolutions offers plans from $695 up to about $1,500. They include resume writing, cover letters, LinkedIn help, and interview coaching. Most clients receive final drafts in five to seven business days.

New AI tools are reshaping how resumes are written. For instance, Career.io Premium charges about $25 per month and offers resume editing, interview practice, and job tracking in one place. The AI system scans a resume, suggests better wording, and checks it against job ads. Many find the dashboard easy to navigate.

On the other hand, Coverlet offers a different approach. Developed for cover letters, it uses large language models to instantly adjust a resume to fit any job description. It rewrites sections, updates keywords, and tweaks formatting within seconds. This saves time and removes some of the personal touch that human writers bring.

With so many providers available, selecting a resume service can be challenging. To make the process easier, focus on a few core areas that matter most: your goals, your budget, the service's track record, and whether they understand your industry.

These steps help avoid services that overpromise but underdeliver. A good resume writer should listen to your goals, ask questions about your past work, and send drafts that reflect your career. Don't rush the process, quality writing takes time, and the right fit makes a real difference.

For freelancers and remote IT workers, choosing the right resume service comes down to clarity, relevance, and time. Many resumes fail not because of weak experience but because they don't match what hiring systems and recruiters look for. Showing completed projects, specific tools used, and contract details can make a big difference.

LA resume writing services like CraftResumes or Resume Writing Lab offer hands-on help and handle the writing process for you. Twine, Fiverr and Upwork are options if you're looking for something more flexible or lower cost. AI tools such as Career.io and ResumeFlow can speed up editing and keyword checks, though they don't always capture the full picture. Whatever option you choose, check that they understand freelance work, can write for IT roles, and send versions you can review. A clear and well-structured resume helps move things forward. more

Career development

 10h

Skills-Based Hiring: The Shift Beyond Degrees - BW People


Prioritising skills over degrees unlocks hidden talent, fuels innovation, and builds a fairer, future-ready workplace

"The best way to predict the future is to create it." -- Peter Drucker

From career counselling webinars to late-night hiring dashboards humming with AI activity, the hiring process is being rewritten in real time. The era of credential-first thinking is giving way to a more... dynamic, inclusive assessment -- focused not on where someone studied, but what they can tangibly do. Degrees are still valued, but they are no longer gatekeepers. They are context, not criteria.

Tech Meets Talent: The Digital Backbone of Skills-Based Hiring

Far from being a silent partner, AI and technology are now centre stage in reshaping how organisations scout and select talent. Algorithms no longer simply scan for keywords -- they decode potential. From intelligent résumé parsers that detect latent abilities to neural network-based models that suggest best-fit candidates based on performance traits, the digital hiring suite has evolved into a cognitive co-pilot.

Tools like Eightfold AI and LinkedIn's Skills Graph are using deep learning to not only recommend talent but to infer learning agility, transferable skills, and job-readiness from unconventional career paths. And this isn't just happening behind the scenes. Applicants themselves are interacting with chatbots that conduct preliminary interviews, VR systems that assess performance in simulated scenarios, and adaptive testing platforms that tailor questions in real time to measure specific competencies.

Technology isn't replacing human judgement -- it's enhancing it. By sifting through vast pools of candidate data and surfacing overlooked gems, it redefines what it means to be "qualified." In this way, the hiring process becomes not only faster, but fairer -- uncovering merit where it was once hidden behind traditional filters.

The Winds of Change

This shift isn't occurring with bluster or bravado -- it's unfolding through precise adjustments in recruitment protocols and cultural perspectives. In 2025, labour shortages bite harder, with 64% of employers struggling to fill roles, particularly in blue- and new-collar sectors like manufacturing, logistics, and tech-driven trades. The old model, tethered to degrees as proxies for competence, falters in a world where technology evolves faster than curricula. A 2023 SHRM report noted that 60% of job seekers now prioritise roles that value skills over formal education, reflecting a cultural pivot toward pragmatism.

This shift is not just practical -- it's philosophical. It questions the rigid hierarchies of traditional hiring, asking: Why should a degree define destiny? By focusing on skills, organisations tap into a broader, more diverse talent pool -- veterans, self-taught coders, gig workers, and those from underrepresented communities who may lack formal credentials but possess raw, practical brilliance. It's a democratising force, levelling the playing field in a world that often tilts toward privilege.

Redesigning Job Descriptions

At the heart of this revolution lies a deceptively simple act: rewriting the job description. Gone are the rote demands for a bachelor's degree "or equivalent experience" tacked on as an afterthought. Companies like IBM and Walmart are pioneering skills-first frameworks, articulating roles in terms of competencies -- critical thinking, adaptability, technical prowess. A 2024 Deloitte study found that 72% of organisations adopting skills-based hiring have revamped their job postings to emphasise measurable abilities over academic benchmarks.

This isn't just semantics; it's a shift in worldview. A job description is no longer a gate but a bridge, inviting candidates to demonstrate what they can do rather than what they have. AI plays a pivotal role here, with tools like Gloat and LinkedIn Skills Insights analysing résumés and portfolios to match candidates' skills to role requirements with surgical precision. These technologies are evolving from gatekeepers to enablers -- mapping complex human abilities with unprecedented clarity and fairness.

Saba Adil, Chief Human Resource Officer, Edelweiss Life Insurance, highlights this evolution:

"Today, companies aren't choosing between specialists and generalists -- they seek individuals who can be both. Deep expertise remains critical, but equally valued is the ability to stretch beyond roles, adapt fast, and contribute across functions. We're seeing a personalised approach to skilling -- empowering employees to grow vertically and pivot into new tracks. It's about unlocking existing potential by shaping roles around evolving skills and aspirations. This shift helps businesses stay future ready while giving people the chance to reimagine -- not just upgrade -- their careers."

Bridging the Gap: Training as Transformation

Skills-based hiring doesn't end with recruitment; it demands a commitment to growth. The skills gap, a chasm widened by rapid technological change, looms large -- Gartner reports that 70% of employees lack the skills needed for their roles in 2025. Organisations are responding with bold investments in upskilling and reskilling, transforming hiring into a cycle of continuous learning.

Vandana Negi, General Manager at NIIT Limited, distils this new paradigm succinctly:

"Skills are the new DNA of talent; focus on the code, not the pedigree. Ability matters more than ancestry."

Take Accenture, which has partnered with platforms like Coursera to offer tailored training in cloud computing and data analytics, empowering employees to evolve alongside their roles. Virtual reality (VR) and augmented reality (AR) are also emerging as tools for immersive learning, allowing workers to hone skills in simulated environments. This isn't just training; it's a philosophical stance that every worker is a work in progress, their potential not fixed but fluid, ready to be sculpted by opportunity.

The Diversity Dividend

Perhaps the most profound impact of skills-based hiring is its promise of equity. By prioritising ability over credentials, companies open doors for those historically sidelined -- women, minorities, and those from lower socioeconomic backgrounds. A 2024 McKinsey study found that skills-based approaches increase diversity in hiring by 20%, as they reduce reliance on networks and institutions that often exclude marginalised groups.

This shift carries a deeper resonance. It challenges the notion that opportunity should be rationed by privilege, affirming instead that talent is universal, waiting only for a chance to shine. In blue-collar sectors, where labour shortages are acute, companies like Siemens are hiring based on hands-on skills, training workers in automation and robotics to meet the demands of Industry 4.0. The result? A workforce that mirrors the world's diversity, rich with perspectives that fuel innovation.

A New Definition of Value

Skills-based hiring is more than a strategy; it's a meditation on value. In a world obsessed with titles and hierarchies, it dares to ask: What makes a person valuable? Is it the degrees they've earned or the problems they can solve? The answer lies in the act of doing -- in the coder who builds a flawless app without a degree, the mechanic who masters robotics through self-study, the leader who inspires through empathy honed in life's uncharted corners.

Yet, challenges linger. Bias in AI-driven hiring tools can creep in, echoing the flaws of human judgement. Upskilling requires resources not all companies can muster. And cultural resistance -- managers clinging to old metrics -- can slow progress. HR leaders must navigate these waters with care, ensuring AI is transparent, training is accessible, and mindsets evolve.

The Road Ahead

As we stand at this crossroads, skills-based hiring invites us to reimagine the future of work. It's a call to see people not as résumés but as reservoirs of potential, each with skills waiting to be unlocked. For HR, it's a chance to architect a world where talent is the currency, diversity the dividend, and growth the goal. In this revolution, we don't just hire -- we transform. more

Career development

 10h

WHY BEBEE IS THE FUTURE OF JOB SEARCHING


Tired of job hunting on linkedin for the job of your dreams? Done with sending cold cover letters to companies you had never heard about? Don't worry. We've all been there, done that. The job market isn't what it used to be, but rather slow, outdated, and impersonal. But hey, modern problems require modern solutions. Meet BeBee- a hybrid employment platform that helps job seekers and companies to... find each other using social features, qualifications, ads and job descriptions.

Traditional Job Boards

* The applicant delivers their submission along with their resume and a cover letter

* The application arrives to an email or inbox for the company to review

* If the company is interested in hiring the applicant, they will contact them (usually) outside of the platform. They schedule an interview, implement a test task or ask further questions

* The job board works as a listing, but doesn't help or improve communication between both parties

BeBee's Platform

* Both job seekers and companies can create public profiles and interact with each other. Also, companies can post newsletters, articles, culture updates and other important information

* Applicants can comment and message companies, even before applying to a job offer

* They both can join communities with shared affinities, facilitating networking processes

* BeBee's mission is to create an integrated environment, implementing a direct and more informal communication, directly on the platform to reduce hiring time.

Agility in Recruiting

With BeBee, you won't have to wait long weeks for a company's response. This platform is fast paced as you can filter by skill the jobs or candidates you want. Here are some other reasons why BeBee just works:

* You can publish without third party approvals

* You'll get real time updates on your applications, as well as a simpler tracking of candidates

* A big plus is that you don't need to switch tools either

* You can find your final candidate or job offer in days

Streamlined Candidate Management

Still tracking candidates in a spreadsheet in excel? Those days are long gone! With BeBee, you'll have all your HR essential features at your hand's reach, in a single dashboard.

* Sort your applicants easily by skill, country, experience, field, etc

* Communicate with them easily on the platform

* Manage their recruitment process entirely without leaving the platform

Be as efficient as possible without stressing!

Built-In Networking

BeBee also has a social aspect to it. Applicants create robust profiles and share content to connect with like minded colleagues from their fields. This isn't just about job applications or job listings, with BeBee you can start to build your own network online. By investing yourself in your industry, your value will rise among companies.

* Networking develops new opportunities for both applicants and companies

* You'll be able to gather information and insights on your chosen field. Also, you can keep yourself updated with competition and workplaces in which you're currently interested in

* Boost your professional profile by putting yourself out there. Work colleagues and companies can get to know you easily.

Content as a Talent Magnet

By creating meaningful content about their respective fields, putting their own brand in the center of it, companies can attract valuable talent. Also, they can showcase their work culture and values. This alone has the power to enhance and enrich their recruitment process as never before.

Did you know that BeBee's PPC model guarantees that each job listing enjoys targeted reach from potentially interested workers? As a company, you can quickly set the budget of your offer, define which type of applicants you want, and grow through impressions/clicks. Don't waste your time anymore with professionals that do not match your required profile. Today's market isn't easy. When HR needs to find a candidate in record time, a platform like BeBee is a life saver.

The platform is really intuitive, so it won't be difficult.

* Create your profile (as a job seeker or a company)

* Write clear job titles, start to create your job listing

* Use PPC settings for niche roles

* Define your target audience using the filters

* Establish the budget

* In under 15 minutes you'll be already attracting applicants and companies

BeBee is a promising hybrid platform, which intertwines direct hiring with networking and PPC filters. This is wonderful for startup companies, as well as small and medium-sized enterprises. Also, by empowering job seekers, they can better their chances of landing in a company they truly love and advocate for. Ready to hire smarter or land your dream role? You can join BeBee today and start building real connections. And keep yourself updated with Island Echo, a place in which we cover the most innovative tools in today's market. more

Career development

 10h

A major AI training data set contains millions of examples of personal data


Thousands of images -- including identifiable faces -- were found in a small subset of DataComp CommonPool, a major AI training set for image generation scraped from the web. Because the researchers audited just 0.1% of CommonPool's data, they estimate that the real number of images containing personally identifiable information, including faces and identity documents, is in the hundreds of... millions. The study that details the breach was published on arXiv earlier this month.

The bottom line, says William Agnew, a postdoctoral fellow in AI ethics at Carnegie Mellon University and one of the coauthors, is that "anything you put online can [be] and probably has been scraped."

The researchers found thousands of instances of validated identity documents -- including images of credit cards, driver's licenses, passports, and birth certificates -- as well as over 800 validated job application documents (including résumés and cover letters), which were confirmed through LinkedIn and other web searches as being associated with real people. (In many more cases, the researchers did not have time to validate the documents or were unable to because of issues like image clarity.)

A number of the résumés disclosed sensitive information including disability status, the results of background checks, birth dates and birthplaces of dependents, and race. When résumés were linked to people with online presences, researchers also found contact information, government identifiers, sociodemographic information, face photographs, home addresses, and the contact information of other people (like references).

When it was released in 2023, DataComp CommonPool, with its 12.8 billion data samples, was the largest existing data set of publicly available image-text pairs, which are often used to train generative text-to-image models. While its curators said that CommonPool was intended for academic research, its license does not prohibit commercial use as well.

CommonPool was created as a follow-up to the LAION-5B data set, which was used to train models including Stable Diffusion and Midjourney. It draws on the same data source: web scraping done by the nonprofit Common Crawl between 2014 and 2022.

While commercial models often do not disclose what data sets they are trained on, the shared data sources of DataComp CommonPool and LAION-5B mean that the datasets are similar, and that the same personally identifiable information likely appears in LAION-5B, as well as in other downstream models trained on CommonPool data. CommonPool researchers did not respond to emailed questions.

And since DataComp CommonPool has been downloaded more than 2 million times over the past two years, it is likely that "there [are]many downstream models that are all trained on this exact data set," says Rachel Hong, a PhD student in computer science at the University of Washington and the paper's lead author. Those would duplicate similar privacy risks.

"You can assume that any large scale web-scraped data always contains content that shouldn't be there," says Abeba Birhane, a cognitive scientist and tech ethicist who leads Trinity College Dublin's AI Accountability Lab -- whether it's personally identifiable information (PII), child sexual abuse imagery, or hate speech (which Birhane's own research into LAION-5B has found). more

Career development

 13h

Kimi K2: The Open Source Way


An anon start-up conducting cutting-edge open-source research on China's science, technology, and industrial ecosystems is looking for part-time China research analysts. You'll be saving America with a firm run by someone I [Jordan] can vouch for being the literal best in the business. Apply here.

A big welcome to , who joined ChinaTalk to cover AI full time this week after three years of... occasional contribution!

Beijing-based Moonshot AI (月之暗面, literally "dark side of the moon" - a Pink Floyd reference) released Kimi K2 on July 11. K2 is a non-reasoning, open source large language model based on the Mixture-of-Experts (MoE) technique and achieved benchmark scores competitive with many leading models, including DeepSeek V3. At 1 trillion parameters, it is an impressive feat. Per Nathan Lambert of Interconnects:

It is a "non-thinking" model with leading performance numbers in coding and related agentic tasks (earning it many comparisons to Claude 3.5 Sonnet), which means it doesn't generate a long reasoning chain before answering, but it was still trained extensively with reinforcement learning. It clearly outperforms DeepSeek V3 on a variety of benchmarks, including SWE-Bench, LiveCodeBench, AIME, or GPQA, and comes with a base model released as well. It is the new best-available open model by a clear margin.

ChinaTalk last covered Moonshot AI in March, when we translated an expansive interview CEO Yang Zhilin (杨植麟) gave to the online tech news platform Overseas Unicorn (海外独角兽). In the conversation, Yang portrayed himself and his company as stubborn AGI purists who focus on "tech visions" rather than product design or short-term revenue generation. K2 is a step towards many aspects of this vision, but its story so far also reflects the jagged reality of cutting-edge model research in China. In this piece we discuss:

Yang Zhilin, born in coastal Guangdong in 1992, earned his bachelor's degree from Tsinghua University and went on to a PhD at Carnegie Mellon. He worked at Meta AI and Google Brain before returning to China to begin his entrepreneurship journey. Unlike fellow Guangdong native Liang Wenfeng (梁文锋), CEO of DeepSeek, Yang has deep connections in both China and the US and does not only focus on hiring domestically educated talent. While Tsinghua is heavily represented in the résumés of Moonshot's founding team, others come from more diverse global educational backgrounds.

Moonshot has no B2B offerings and does not build wrapper tools for corporate users, instead focusing directly on individual customers. From the beginning, Kimi's selling point to Chinese users was its long context window, allowing users to upload dozens of documents and analyze long articles. But it's not just about an awesome user experience; long-context is central to Yang Zhilin's AI worldview. Per his comments in the Overseas Unicorn interview:

To achieve AGI, long-context will be a crucial factor. Every problem is essentially a long-context problem -- the evolution of architectures throughout history has fundamentally been about increasing effective context length. Recently, word2vec won the NeurIPS Test of Time award. Ten years ago, it predicted surrounding words using only a single word, meaning its context length was about 5. RNNs extended the effective context length to about 20, LSTMs increased it to several dozen, and transformers pushed it to several thousand. Now, we can reach hundreds of thousands.

Yang's previous venture Recurrent AI (循环智能) was funded by seven venture capital firms, two of which also invested in Moonshot. Alibaba became Moonshot's biggest backer in 2024. As Moonshot's valuation rose rapidly, five of Recurrent AI's investors -- those who did not join Moonshot's funding rounds -- filed an arbitration case against Yang, alleging that Moonshot was launched without obtaining necessary waivers from previous investors. Recall that High Flyer, the parent company of DeepSeek, is a hedge fund, and that Liang Wenfeng has rejected outside investment as of March. Moonshot operates under much more normal tech startup restraints and faces investor pressure. Still, with just $1 billion raised (much less than the likes of Anthropic and OpenAI) and pressure to ultimately deliver value to shareholders, it created a leading open model, rather than operating in the hedge fund-funded cocoon that DeepSeek researchers enjoy.

What we are starting to observe here is rather obvious in hindsight, as we move farther away from the DeepSeek moment: there is no single path to success for Chinese frontier labs. One does not necessarily have to replicate the DeepSeek recipe, whether in terms of hiring, funding, or labor practices, to create world-class models. Compute constraints, which apply across China, continue to incentivize a diverse range of research teams in China to pursue novel algorithmic research.

The team behind Kimi is very active on Zhihu (知乎), China's Quora equivalent. According to a post by engineer Liu Shaowei (刘少伟), K2 essentially copied the combination of Expert Parallelism (EP) and Data Parallelism (DP) outlined by DeepSeek in V3's technical report, with four notable changes:

Recall Yang Zhilin's Overseas Unicorn interview, where he argued that "AI is essentially a pile of scaling laws laid on top of each other". Raising the number of experts seems to reflect that. As for why they used DeepSeek's architecture, Liu says there was no point reinventing the wheel:

Before starting to train K2, we conducted a large number of scaling experiments related to model architecture. The result was that none of the proposed architectures at the time were truly able to outperform DeepSeek V3. ... The reason is simple: the V3 architecture has been validated and remains effective at large scale, whereas our "new architectures" haven't yet undergone sufficient large-scale validation. Given the presence of two massive variables -- Muon optimizer and a much larger model size -- we didn't want to introduce additional unproven variables just for the sake of "being new."

Another Zhihu comment by fellow Moonshot engineer Su Jianlin (苏剑林) highlight other ways K2 learned from DeepSeek (italics added by editor):

Internally, we were also constantly exploring better alternatives to MLA [multi-latent attention, an architectural idea refined and scaled by DeepSeek], but since this was our first open-source large-scale model, we ultimately chose to pay tribute to DeepSeek by replicating its MLA design.

As for the MoE (Mixture of Experts) component, we adopted DeepSeek-V3's shared expert, high sparsity, and loss-free load balancing. ... A special note on the Sparsity part: for quite some time, we were running experiments with Sparsity = 8 (i.e., selecting 8 out of 64 experts). It wasn't until we resolved some infrastructure issues one day that we began trying higher sparsity levels and found the gains to be significant. So we started exploring the Sparsity Scaling Law and gradually leaned into configurations similar to DeepSeek's projections (DeepSeek-V3 already uses 256 choose 8, 32 Sparsity; while K2 uses 384 choose 8, 48 Sparsity). It felt like fulfilling a prophecy that the DeepSeek team had already made.

K2 would not exist without DeepSeek -- and without an open-source culture and free flow of research. While Moonshot and DeepSeek are certainly competitors at the corporate level, Kimi's engineers express deep respect for their DeepSeek colleagues. Yang Zhilin, in February 2024, had told Tencent News that he didn't believe open source models could catch up to closed source any time soon, because "many open-source contributions may not have been validated through compute-intensive testing," while closed-source projects "attract concentrated talent and capital." Moreover, he remarked that if he had a leading model today, "open-sourcing it would most likely be unreasonable ... it's usually the laggards who might do that -- or they might open-source a small model just to stir things up." So what changed between then and now? The success of DeepSeek was probably an important proof-of-concept for open source for fellow Chinese AI entrepreneurs. While Yang himself has yet to offer any updated comments on his open-source views, Moonshot engineer Justin Wong shared his "why open source" take on Zhihu:

First of all, we obviously wanted to gain some recognition. If K2 were just a closed-source service, it wouldn't be getting nearly as much attention and discussion as it is now. ...

Next, open-sourcing allows us to leverage the power of the developer community to improve the technical ecosystem. Within 24 hours of our release, the community had already implemented K2 in MLX, with 4-bit quantization and more -- things we truly don't have the manpower to accomplish ourselves at this stage.

But more importantly: open-sourcing means holding ourselves to a higher technical standard, which in turn pushes us to build better models -- aligned with our goal of AGI.

This might seem counterintuitive -- if we're just releasing model weights, why would that force the model to progress?

The logic is actually very simple: open source means performance comes first. You can no longer rely on superficial tricks or hacks to dazzle users. Anyone who gets the same weights should be able to easily reproduce your performance -- only then is it truly valid.

With the success of DeepSeek, Chinese frontier labs now have ample, proven justification for the value of open source, both for marketing and in terms of research relevance.

Moonshot calls K2 "open agentic intelligence". It's not just an OpenAI pun; the K2 team is trying to make their mark by refining definitions of agentic capabilities. Justin Wong frames the importance of agents as such:

A while ago, when agent products were all the rage, I saw a lot of comments saying that Kimi should stop competing in the arena of large models and pivot to making agent products. I just want to say that most such agent products are nothing without Claude. Windsurf being cut off from Claude further proved my point.

Fellow Moonshot engineer and Zhihu user Flood Sung created the following diagram to visualize K2's agent vision:

Sung explains:

We first let the model generate hundreds of scenarios such as food delivery, Weibo, WeChat... Then based on the scenarios, we generate thousands of tools, such as ordering food delivery, sending Weibo posts, [and] finding contacts. Then based on different tool combinations, we generate hundreds of thousands of different agents (different system prompts + different tool sets). Next, we design tasks ranging from simple to complex with scoring points for each different agent. Then we begin large-scale agent simulation: first assign tasks to a simulated user, let the user interact with the corresponding agent based on the task, and the user is also generated with different personalities and language styles. Next, the tools called by the agent are also simulated through a tool simulator, which is actually equivalent to a world model to execute and return feedback to the agent for continued processing. After executing the entire task, we use the scoring points from the judgment criteria to evaluate whether the agent's interactions meet the requirements. Good data is then stored!

In other words, K2 was trained on massive amounts of synthetic data, generated specifically to resemble real-life applications and optimized for tool-calling.

On the technical front, the Kimi team wants to expand on their current vision for agentic capabilities and build "large scale agentic RL." Of course, they also want to move out of the shadow of DeepSeek's infrastructure and eventually pioneer their own scalable approaches. We might expect a reasoning model based on K2 in the near future, as well as future foundational models.

Reading through Yang Zhilin and Moonshot engineers' comments, one might get the impression that they are dismissive of wrappers and applications. But that's not the whole truth. To understand their approach to real-life application, one has to take into account both the company's AGI-centric worldview and their theory of change. Yang Zhilin, in his Overseas Unicorn interview, said that the secret ingredient to transformative AI was trust:

I think the ultimate measure of an AI product's long-term value is how much personalized information users are willing to input into it, and then lossless long-context and personalization are responsible for turning these inputs into valuable outputs. New hardware forms may also be needed -- but I think models and software are still bottlenecks. To dig deeper, the prerequisite for users to input a lot of information is trust -- you need a sufficiently engaging and human-like AI. You can't say, "I'm setting up product features specifically to get your information." The end result should be that users and AI become friends, so users can tell the AI anything.

Justin Wong riffs on why this means moving away from the chatbot experience in his Zhihu comment:

Your interaction process with AI is not about directly outputting a piece of content, but rather understanding the user's needs and immediately starting a small project [or] delivering a frontend application. Users can continue to ask questions, modify, and iterate, but all of this revolves around a deliverable.

Sharp-eyed friends may have already noticed -- isn't this just Cursor/Aider/OpenHands? Wrong. From an implementation perspective, this is indeed AI programming. But if designed cleverly in the product, you can hide the code-writing process. Then, for users who don't understand programming, this becomes 'I talked to AI, and it actually made me a PowerPoint/drew a flowchart/wrote a mini-game'. ... This is a completely superior experience to traditional chatbots. ... I believe Kimi products will soon have some surprising changes."

"AGI", according to the team behind Kimi, has to feel like AGI. We should probably not expect Moonshot to put out wrapper products, especially since K2 is not multimodal, but the company certainly hopes to change how regular users experience AI usage in the near future.

What does K2 mean for competitors in the West? To quote Nathan of Interconnects again, Western labs like OpenAI, which has delayed release of its own open-weights model, are losing narrative control in open source.

We need leaders at the closed AI laboratories in the U.S. to rethink some of the long-term dynamics they're battling with R&D adoption. We need to mobilize funding for great, open science projects in the U.S. and Europe. Until then, this is what losing looks like if you want The West to be the long-term foundation of AI research and development.

K2 shows that DeepSeek wasn't a wild exception to the rule or entirely a product of unique circumstances. Here is a startup with founders from different backgrounds, a more traditional VC funding structure, and different philosophy on AI who was also able to achieve a highly competitive open model, likely with strong uptake by users.

As for what's next for Moonshot the company? Yang Zhilin gives few media interviews and eschews politics, and state media is yet to comment on K2. It would be a surprise if he immediately got the State Council treatment Liang Wenfeng did. Both Baidu and Tencent quickly integrated DeepSeek's models into their products. K2 offers yet another cost-efficient option for big internet platforms looking for AI integration; its apparently strong creative-writing capacities might especially appeal to platforms like Weibo (similar to Twitter/X) and Xiaohongshu/Rednote (similar to Instagram).

Like DeepSeek, however, Moonshot is unlikely to try to broaden its user base through actual partnerships with internet platforms in China. Playing the platform-capitalism game was a point of frustration for earlier iterations of Kimi. Moonshot was the top spender on ads among AI firms in China in 2024, according to ad analytics firm AppGrowing:

The aggressive strategy caused controversy online, with users on Bilibili (similar to YouTube) and Kuaishou (similar to TikTok/Douyin) complaining about the endless volumes of Kimi ads they saw in feeds.

In February 2025, Moonshot eliminated most of its ad placements on third-party platforms to focus resources on developing its foundational model. Justin Wong says that what DeepSeek proved to the rest of the industry was that "capability was the best form of advertisement": "[DeepSeek] showed that the path we all believed in was not just viable, but actually a wonderful route to real success. Our only regret was that we were not the one to open up that route." From the DeepSeek moment to now K2, foundation model-focussed startups have carved out a modus operandi in China's AI landscape.

Finally, Chinese users will obviously cheer for yet another competitive domestic model, but will others around the world take up K2? The model is, of course, compliant with Chinese laws, and you won't be able to learn about Tiananmen from the chat interface. This is me trying to have a conversation with K2 about 1989 -- note how it pulls sources, and then hesitates:

Perplexity has announced that it will soon begin post-training K2 to make it available to its users. This means that like with DeepSeek R1, an uncensored version of K2 will be available through Perplexity. For now, platforms like Perplexity have plugged the political censorship challenge facing global adoption of Chinese LLM chatbots.

I played around with Kimi intermittently for a day. Its "tone" strikes me as factual, reserved, and extremely careful, a subtly different experience from using "glazey" ChatGPT or the ever-cheerful Claude. At various points, I was even annoyed by the way it replied to inquiries curtly. I tried having the same silly conversation about vestigial organs ("has anyone out there ever had every useless part removed from their body") with Claude, DeepSeek, and Kimi, and Kimi was the only model that did not proactively try to engage me further, displayed no inkling of speculation, and did not even use any exclamation marks to signal pleasantness!

Perhaps being a model that chooses words carefully has its benefits. K2 topped benchmarks for creative writing. Commentators have been noting its refreshing style, command of vocabulary, and narrative cohesion. Here are two poems from Kimi, one in English and the other in Classical Chinese.

Prompt: Write me a 15-line poem in the style of Mary Oliver about open source software

Prompt: 写一首有关旧金山市景的唐诗 [Write me a Tang Dynasty poem about scenery in the city of San Francisco]

Dawn over San Francisco

(regulated heptasyllabic verse)

At daybreak, Golden Gate fog dampens the streaming flags,

power cables stitch the sky, carrying the ocean's roar.

Scarlet trestles span the waves, hiding kingfishers like jade,

vermilion towers catch the sun, cradling clusters of grapes.

Wind flips tavern pennants -- thousand banners alive,

after rain the flowered terraces blaze in five bright hues.

Who stands atop the hill to hear the dusk drum?

A distant bell -- one single stroke -- falls through a robe of cloud.

[Jordan] It wrote me a spectacular short story about the US trading H20s for rare earths. The prompt was "write me a 500 word story in the style of david foster wallace about the us and china doing a deal to exchange rare earths for H20 chips"

Picture, if you will, one of those late-summer Beltway afternoons when the sky over D.C. looks like a migraine -- white, swollen, vaguely nauseous. Inside the EEOB, the air-conditioning is thrumming at that pitch that makes your fillings vibrate. Deputy Undersecretary for Strategic Stuff Lyle "Chip" Ketchem -- who insists the nickname predates the semiconductor industry by decades and is therefore ironic -- stands before a wall of LCDs displaying supply-chain heatmaps in colors not found in nature. The maps are supposed to convey urgency, but they mostly convey the sense that someone has spilled lava on a Lite-Brite.

Across the table: Minister-Counselor Wen Jieru, whose business card identifies him, in bilingual serif, as "Senior Coordinator for Reciprocal Resource Harmonization." Wen has the kind of face that looks polite even while calculating the exact cubic meters of your personal failure. Between them sits a single legal pad upon which someone has written, in bureaucratic uncial, "MOU: H₂O ⇄ REE." Below that, a subordinate has added, in smaller letters, "(no jokes about water boarding, please)."

The deal itself is almost comically symmetrical, like a grade-school barter of a peanut-butter sandwich for a pudding cup, except the sandwich is a wafer of circuitry etched at 1.4 nanometers and the pudding cup contains dysprosium, terbium, and enough praseodymium to make every iPhone in Shenzhen vibrate with joy. The U.S. will ship, over 36 months, one hundred thousand "H₂O" neuromorphic chips -- so named because their architecture supposedly mimics the lateral geniculate nucleus of a freshwater trout, or so claims the marketing deck, which no one has read past page 4. In exchange, China will release, in quarterly allotments, thirty-seven metric tons of rare-earth oxides that currently sit in bonded warehouses in Guangxi like extremely expensive decorative gravel.

Chip tries to frame the swap as a triumph of interdependent resilience. Wen listens with the expression of a man auditing a children's recorder recital. When Chip invokes "win-win," Wen replies, in perfect MBA English, "Wins are scalar, not vector. Direction matters." No one laughs, because laughter is not on the agenda. Instead, they proceed to Attachment 7-B, subsection (iv): "Protocols for Geopolitical Optics." This is the part where each side agrees to describe the other as a "valued partner" while simultaneously briefing their respective media that they have "held firm on core equities." The linguistic gymnastics make Chip feel like he's chewing aluminum.

They break at 19:27 for individually wrapped sandwiches whose ingredient lists read like passwords. Wen peels the sticker off his turkey-swiss and folds it into a tiny paper crane, which he places on the edge of his plate like a punctuation mark. Chip stares at it, suddenly aware that the crane is the only object in the room with no hidden agenda. He experiences a moment of vertiginous clarity: the chips will be obsolete before the last shipment clears customs; the rare earths will be stockpiled in a Nevada salt cavern until some future administration rediscovers them and tweets about strategic surprise. The swap is not about materials at all; it is about the narrative that materials can be swapped. The story is the commodity.

Back in the conference room, the LCDs refresh. A new heatmap blooms -- magenta, viridian, arterial red. Chip signs. Wen signs. Cameras flash like paparazzi at a funeral. Outside, the sky has ripened to a shade that Pantone has not yet named, but will eventually market as "Imminent Dusk."

ChinaTalk is a reader-supported publication. To receive new posts and support our work, consider becoming a free or paid subscriber. more