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# Meshy Expands AI-Assisted 3D Workflow to Support Faster Early-Stage Product Visualization. San Francisco, California, United States, July 2, 2026 -- Meshy, an AI-powered 3D content platform, today announced continued expansion of its AI-assisted 3D creation workflow to help startups, product teams, designers, and creative professionals accelerate early-stage concept visualization through faster generation of three-dimensional assets from text prompts and images. The expanded workflow reflects increasing demand for tools that simplify concept visualization during the earliest phases of product development, when businesses often need to evaluate multiple ideas before investing in engineering, manufacturing, or production-ready modeling. Rather than replacing traditional CAD software or professional engineering workflows, Meshy's platform is intended to complement existing design processes by helping teams communicate ideas earlier and more efficiently. As part of its ongoing platform d

Specialized models trained on product interaction data can change UX quality, latency, and cost trade-offs compared with generalist frontier models. According to Wix's corporate blog, Base44, acquired by Wix in June 2025, has launched a proprietary LLM called Base1 to power its vibe-coding app-creation workflow. TechCrunch and other outlets report the model was trained on a dataset derived from "tens of millions of real user interactions on the platform" (TechCrunch) and that Base44 will use reinforcement learning in ongoing tuning (Business Insider). TechCrunch reports the model was developed from a dataset generated by **"tens of millions of real user interactions on the platform"** and that the release is being rolled out to users (TechCrunch). **Technical context and training approach**, Reported facts and sourcing: TechCrunch and Aixploria describe Base1 as a model fine-tuned and trained on Base44's product data, with reinforcement learning used to push the model toward more varie

# Meta names Alex Schultz first-ever chief data officer. Meta has named its chief marketing officer, Alex Schultz, as its new chief data officer, Schultz told Axios. * The company's vice president of consumer marketing and growth Denise Moreno has been elevated to CMO. **Zoom in:** In his new role, Schultz will be tasked with transforming how the company manages AI analytics across the company globally. * As part of that effort, he will continue managing the company's infrastructure analytics teams. * Both Schultz and Moreno will report to Meta chief operating officer Javier Olivan. **What's next:** In an interview, Schultz said the "context layer" of Meta's AI system — or the organizational knowledge that gives AI models the ability to reason accurately — will be key to building's Meta's data analytics infrastructure. * Building a "semantic" layer across Meta's data warehouse that can help the company interpret its data across all products will be a top priority for the next six month

# Russian Gasoline Prices Rise Again After Ukraine Hits Refineries. Provide news feedback or report an error. Send a tip to our reporters. ## **Takeaways** by Bloomberg AI. Retail fuel prices in Russia notched up another significant increase as recent Ukrainian drone strikes on the country’s oil refineries have led to a nationwide gasoline shortage, long lines at pumping stations and renewed concerns about accelerating inflation. Average gasoline prices across the country rose about 1.7% on the week to 72.38 rubles ($0.93) per liter in June 23-29, according to data from the Federal Statistics Service released Wednesday. The advance follows the biggest increase last week in at least 20 years. Before it's here, it's on the Bloomberg Terminal.

## Skills SA to treat multi-agent workflow as a reusable pattern ## US removes curbs on Anthropic's latest Fable and Mythos AI models ## ACCC rules on Vodafone's Telstra coverage complaint ## Nexon Asia Pacific builds customer trust with certification to international AI standard ## Service NSW appoints interim chief digital officer. Skills SA has built a multi-agent AI workflow to help it review how well vocational education and training providers meet a set of student support requirements each year. The setup, running largely on a Databricks stack, has the makings of a pattern that would be applicable to a broad range of other government enterprise processes, and reuse inside of Skills SA is already on the cards, according to AI, data and integration lead Jarrad Taylor. Speaking at the Databricks Data + AI Summit in San Francisco, Taylor said the initial use case is to help assessors review responses to an annual compliance process for VET training providers, known as the Organisatio

# Less Than Half of Organizations Can Reliably Tell If There‘s a Real Person Behind an Online Identity Check. RESTON, Va., July 01, 2026 (GLOBE NEWSWIRE) -- **While most organizations have tools to verify human presence, only 48% fully trust them.** **The latest Regula survey,** ***The New Shapes of Identity Threats 2026*** **, highlights that AI-assisted automation, deepfakes, and generated identity evidence are changing what businesses need from identity verification. Now it is not just a pass-or-fail result, but proof that a real person was present and the evidence was authentic.**. AI is becoming an active participant in digital interactions, making it increasingly difficult for organizations to determine who — or what — is behind an identity verification attempt. *Regula survey states that more than half**of organizations cannot confidently prove that a real person is behind an online identity check*. More than half of organizations (52%) cannot fully verify that biometric data w

# In a First For Science, A Satellite Has Identified What It's Seeing From Space. The standard approach to satellite imagery is to snap huge batches of pictures and beam them back to Earth, where they can be sifted through by human operators and the best available algorithms. However, the YAM-9 satellite has just done something different: It has identified and described features in its image scans without needing to check back with ground control. Not only that, but it can be instructed with natural prompts that you might use with Google Gemini or Siri, such as "find me all the railway hubs in this country". Most of the time, when you interact with an AI chatbot like Claude or ChatGPT, your queries are sent to energy-intensive data centers, where they are processed and a response is sent back. By housing AI models on a device instead, the processing is much faster without that back-and-forth, and if you're a satellite, that means less need for ground communications.

### AI tools can give CMOs time to focus on taste and judgment, says Reddit's Jim Squires. # How 6 top CMOs are working to make their brands show up on AI platforms. But make no mistake — CMOs are looking to make sure their brands show up in AI search in the right way. "Everyone's talking right now" about going from traditional search to AI search, Chime's Vineet Mehra said. I asked a selection of Business Insider's most innovative CMOs of 2026 how they're honing their AI visibility strategies. Top marketers like Bobbie's Kim Chappell and Coach's Joon Silverstein are also producing more content across Substack, YouTube, and their own websites for LLMs to draw on for their answers. SEO pros also said brands should pay attention to how they show up in Reddit and YouTube, which are highly cited in AI results, while cautioning that it can be hard for brands to avoid the self-promotional spiel that's unwelcome on Reddit.

The company is already profitable, with annualized run-rate revenues of over $70 million, its CEO Erik Voorhees (pictured above, in the center) told TechCrunch during an exclusive interview. Understandably, investors have flocked to get a piece of that traction. Venice AI on Wednesday said it had raised a $65 million Series A at a $1 billion valuation, its first external fundraise. The round was led by crypto-focused venture firm Dragonfly, with participation from Coinbase Ventures, North Island Ventures, and others. [...] REGISTER NOW ## Most Popular Flipper Device’s new Busy Bar is a customizable display for productivity + Ivan Mehta Ford rehires ‘gray beard’ engineers after AI falls short + Anthony Ha Govee’s smart nugget ice maker makes every iced drink feel like a luxury + Aisha Malik Asian AI startups launch Mythos-like models as Anthropic’s export ban drags on + Kate Park FTC gives Musk the OK to acquire SpaceX alumni startup Mesh + Marina Temkin Trump ad

The round was led by Aramco Ventures, with participation from Vista Equity Partners, General Catalyst, Emergence Capital, Nvidia, March Capital, Pegatron, SentinelOne’s S Ventures and others. Together AI last raised a $305M Series B at a $3.3 billion valuation about 16 months ago. It actually came out of gate well funded, with a $102.5 million Series A funding round led by Kleiner Perkins with participation from Nvidia and Emergence Capital back in 2023. There were whispers of this round back in March, when The Information reported that the company was seeking $1 billion in funding, but at a $7.5 billion valuation. So, if the numbers in that report were accurate, that means that Together AI took less money, but perhaps got a better deal from VCs than it had been pursuing in the spring. [...] That means that neoclouds, which are the companies providing AI-specific hardware (often Nvidia GPU clusters) and other infrastructure tools, have been hot commodities for VC investment. Upscale

Skip to main content Axios Pro Exclusive Content # Exclusive: Fabless chip company Stathera closes $55M Series B Chris Metinko 3 hours ago Stathera, a fabless semiconductor company specializing in silicon timing solutions, raised a $55 million Series B led by new investor Maverick Silicon, co-founder and CEO George Xereas tells Axios Pro exclusively. Why it matters: Data center performance relies on how quickly and effectively data can move and remain synchronized across tens of thousands of processors. ##### What to read next

Etched, founded in 2022, also revealed that it has now raised a total of $800 million to date. The most recent tranche was an unannounced $500 million round closed in December at a $5 billion post-money valuation, the company said. The startup has attracted a notable group of investors, too, including VentureTech Alliance, Jane Street, Hudson River Trading, Two Sigma, and Ribbit Capital. It has also secured angel investment from AI heavyweights including Andrej Karpathy, Geoffrey Hinton, Fei-Fei Li, Arthur Mensch, and Scott Wu. The cap table also includes billionaires Stanley Druckenmiller and Peter Thiel. [...] By 2024, Etched was already on investors’ radar, having raised more than $125 million. But on Patrick O’Shaughnessy’s “Invest Like the Best” podcast, the founders said that back in 2023, they struggled to get investors interested — even with a 30-page memo arguing that AI would eventually need specialized chips, not just general-purpose GPUs. Every major investor they pitched

If you want your shot, applications close in just a few days on July 6. In 2017, Manuri Gunawardena was a final-year medical student when she pitched HealthMatch, a machine learning platform matching patients to clinical trials. She won Startup Battlefield Australia. That single moment helped propel HealthMatch to more than $25 million raised, expansion into the United States, and over 1 million patients served globally. The runner-up, FluroSat, used the exposure from that same stage to secure a Microsoft seed round before ultimately becoming part of Regrow Agriculture, which has now raised more than $60 million and counts Microsoft, Airtree, and Cargill among its backers. [...] ### Topics Biotech & Health Cloud Computing Crypto Enterprise EVs Fintech Fundraising Gadgets Gaming Google Government & Policy Hardware Instagram Layoffs Media & Entertainment Meta Microsoft Privacy Robotics Security Social Space Startups TikTok Transportation Venture ### More fro

“Second, AI-powered software is enhancing robot capabilities and ease of use, enabling robots to perform tasks they previously couldn’t, thereby creating demand in markets that were difficult to penetrate,” she added. The introduction of AI has improved industrial robots’ visual guidance and made them easier to programme and better at co-ordinating with others. AI has also enabled remote monitoring and maintenance of robots, she wrote. [...] Sany’s No.18 factory, opened in 2012, is one of the planet’s largest “lighthouse factories”, a World Economic Forum designation given to particularly smart manufacturing bases. With recent improvements in AI, the factory has continued to innovate, says Peng: “it makes us much more efficient”. For instance, it previously took a number of humans to manually sort through the array of metal frames delivered to the factory’s eastern end. But with the advent of AI, the factory’s robotic arms can identify the shape and weight of the parts, decide which

Accessibility Statement Skip Navigation # Straiker Raises $64M Series A to Secure the Agentic Workforce ## News provided by Straiker Jun 29, 2026, 08:03 ET ## Share this article Share toX Share this article Share toX Round led by Marathon with continued support from Bain Capital Ventures and Lightspeed. Trusted by Fortune 500 enterprises and Frontier AI labs, the company defends the fastest-growing workforce in the enterprise: AI agents. [...] That traction has translated into rapid commercial growth. In less than a year, Straiker has grown run-rate revenue by more than 15x, reflecting accelerating demand for security built for autonomous systems. "Demand is outpacing anything we forecast," said Ankur Shah, Co-Founder and CEO of Straiker. "This round goes straight into product, our STAR Labs threat research, and the global expansion our enterprise customers are pulling us toward." "Given their scope and autonomy, AI agents need to be treated like first-class citizens," sai

Omen AI has a solution: A tiny spectrometer that can monitor that fluid health in real time, spotting bacterial growth before it becomes a massive problem. “You’re not risking huge amounts of downtime because you have no insight into what’s going on chemically,” explains CEO and founder Zach Laberge. Today, Omen AI said it raised a $31 million Series A round, led by Nava Ventures and including participation from CRV, Vanderbilt University, Mann+Hummel, Starhill Holdings, Hard Launch Capital, as well as personal investments from executives at Bridgestone, GM, Johnson Controls, and Tensorwave. [...] + Jagmeet Singh OpenAI unveils its first custom chip, built by Broadcom + Russell Brandom HaloBraid raises $7M from Seven Seven Six to end the six-hour hair salon appointment + Dominic-Madori Davis Loading the next article Error loading the next article [...] View Bio November 4 Boston Last chance to save up to $190 on TechCrunch Founder Summit. Join 1,000+ founders and VCs at a

Flow Matching (FM) has emerged as a powerful paradigm for speech generation but remains constrained by high inference latency and timbre leakage. To address these bottlenecks, we propose a unified guidance framework that enhances generation efficiency and robustness through two complementary strategies. On the data front, we introduce Data-guidance via heterogeneous augmentation, encouraging the model to disentangle linguistic content from acoustic residue. In parallel, we propose an enhanced Model-guidance mechanism that synergizes trajectory rectification with a novel intrinsic guidance objective. This approach distills conditional knowledge into network weights and straightens inference trajectory path, thereby eliminating Classifier-Free Guidance (CFG) overhead. Experiments demonstrate that our framework accelerates inference by nearly three times while effectively improving speaker similarity compared to state-of-the-art baselines.

This paper presents Speech Playground, an interactive speech visualization and comparison tool. While existing tools such as Praat are excellent, it can be cumbersome to integrate them with modern deep learning representations and use them for comparison. Speech Playground addresses this by combining a Python backend with a web-based frontend for interactive exploration of multiple feature types, including continuous, discrete, and variable-length representations. It includes TextGrid and forced alignment support together with configurable distance and alignment settings for visual and auditory comparison. Speech Playground is intended for use in speech research, representation validation, and computer-aided pronunciation training (CAPT)-oriented experimentation.

Audio-visual feature extraction is a fundamental component of multimodal understanding and generation tasks. However, existing evaluation protocols for feature extraction models exhibit dimensional bias, typically focusing on either semantic matching or temporal offset detection. Moreover, their data construction remains coupled, preventing independent assessment of temporal and semantic consistency. We propose AV-SyncBench, the first benchmark to fully separate temporal and semantic evaluation for audio-visual synchronization. Built from in-the-wild videos, it spans Voice, Music, and Sound across 10 scenarios and 5 challenge tasks. Data are automatically filtered and manually verified to ensure on-screen sound sources. The benchmark contains 3,269 videos and 38,390 samples, and we evaluate five representative models to quantify feature quality for alignment and downstream tasks. The code and dataset are available at: https://fgt7t6g.github.io/AV-SyncBench.

Recognizing jazz standards from audio is a challenging form of tune-level music retrieval: different performances of the same standard may vary in tempo, key, arrangement, instrumentation, improvisational content, and even whether the head melody is present. We study this problem using a curated subset of the Jazz Trio Database designed for cross-performance standard recognition. We compare a from-scratch trained Harmonic CNN baseline against frozen pretrained music representations from recent music understanding foundation models, using both supervised probing and nearest-neighbor retrieval. Our results suggest that from-scratch spectrogram models overfit strongly to training performances, while pretrained embeddings provide better top-$k$ results but are sensitive to performer identity, which can be partially reduced with a lightweight contrastive projection. Our findings motivate jazz standard recognition as a useful stress test for music representation models and as a step toward r

While prior work has explored emotion control in hybrid text-to-speech systems, the geometric properties of these modules, and their implications for steerability, remain poorly understood. We present the first comparative study of speech language model (SLM) and conditional flow-matching (CFM) modules as activation steering sites for mixed emotion speech synthesis. We first characterize emotion representations using linear probing and local intrinsic dimensionality (LID), and then evaluate single-site and joint steering for mixed-emotion synthesis. Our results show that SLM offers a clean, low-dimensional emotion-specific subspace with strong speaker--emotion disentanglement, while CFM exhibitspoor cross-speaker generalization due to speaker--emotion entanglement. Joint steering increases emotion intensity but degrades proportional control and speech quality on in-distribution data. These findings provide practical guidance for multi-site activation steering in hybrid TTS systems and

We present NPUsper, a live transcription system that makes Whisper efficient on mobile NPUs by eliminating redundant computation. To avoid the heavy padding used by prior streaming systems, NPUsper detects hallucinated tokens online from temporal patterns in decoder cross-attention, allowing each inference round to process short audio inputs with minimal carryover. For efficient mobile-NPU execution, we propose controlled unrolling, which executes autoregressive decoding as K-step chunk graphs, removing unnecessary KV-cache computation and reducing graph-dispatch overhead. NPUsper achieves up to 4.84x lower per-word latency, up to 33.2x lower time-to-first-token (TTFT), and up to 88.64% lower average power consumption compared with baselines, while maintaining comparable transcription accuracy. The code is available at https://github.com/npusper/NPUsper.

Repository-level performance-optimization benchmarks such as GSO, SWE-Perf and SWE-fficiency evaluate coding agents by applying patches to real repositories and comparing runtime against unoptimized baselines and official reference patches. Their leaderboard scores are increasingly used as evidence of coding-agent progress, but those scores can conflate runtime instability, benchmark-specific scoring rules, and how many tasks are already solved by at least one public submission. We audit these issues across the three benchmarks. First, we replay the official reference patches for 740 code optimization tasks across four common types of Google Cloud machines. Most benchmark tasks can be replayed, but their reference patches satisfy the original benchmark validity rules in every cross-machine replay for only 39/102 GSO tasks, 11/140 SWE-Perf tasks, and 411/498 SWE-fficiency tasks; SWE-Perf is especially fragile because many reference patches produce close-to-zero runtime changes. Second,

We present a real-time musical interface that converts natural-language scene descriptions into evolving procedural soundscapes. A performer types a prompt such as "warm jazz cafe at midnight" and steers it through direct parameter adjustments - stepping brightness down, switching a rhythm style - each producing a predictable, audible shift without re-prompting. Where GPU-bound text-to-audio systems synthesize monolithic waveforms, our instrument generates human-readable configurations over a categorical schema, enabling fine-grained performer control; most valid combinations are designed to sound musically coherent. Three interchangeable backends - embedding retrieval for sub-second CPU-only use, hosted LLMs via API, and a fine-tuned 270M local model - all emit the same schema. A live generator architecture continuously emits audio while resolving new instructions in the background, crossfading seamlessly when ready; even when an LLM takes 5-12 seconds to respond, the audience hears u

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1y Report this comment Precisely the point. You have just nailed it. Btw, these AI organisations in Kenya have a deliberate approach in terms of who they recruit in their organisations as data workers. They recruit guys from the informal settlements. Young people who are desperate for work. Young people who will not question the integrity of why things are being done the way they are done. But then if you get the audacity to do so (question them), then and only then does your contract get terminated. Ridiculous, isn't it? But is I said the other day, a lie can only be defended briefly by certain people, but when the truth is unravelled, we will be there no matter what. LikeReply15 Reactions 16 Reactions Image 10: kisembo hannington, graphic [...] For years I’ve been interviewing d

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Create a Job Alert Interested in building your career at Anthropic? Get future opportunities sent straight to your email. ## Apply for this job \ indicates a required field Accepted file types: pdf, doc, docx, txt, rtf How do you pronounce your name? We believe that AI will have a transformative impact on the world, and we’re seeking exceptional candidates who collaborate thoughtfully with Claude to realize this vision. At the same time, we want to understand your unique skills, expertise, and perspective through our hiring process. We invite you to review our AI partnership guidelines for candidates and confirm your understanding by selecting “Yes.” Why do you want to work at Anthropic? (We value this response highly - great answers are often 200-400 words.) [...] Your safety matt

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. [...] Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/ca

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