SINGAPORE, Jan. 30, 2026 /PRNewswire/ -- As the Lunar New Year approaches, JM Flower invites Singaporeans to discover purposeful and beautifully curated CNY gifts that bring heartfelt blessings and lasting impressions to loved ones, clients, and event guests. From festive floral arrangements to thoughtfully designed CNY hampers, this year's collection embraces tradition with contemporary style and convenience.
With Chinese New Year gift-giving deeply rooted in the symbolism of prosperity, luck and harmony, JM Flower's seasonal offerings elevate every celebration with meaningful selections that reflect festive sentiments. Now live online, shoppers can explore the full range of premium products at https://jm.com.sg/collections/cny-gifts-hampers - featuring bespoke gift sets, elegant floral arrangements, luxury hampers and more.
Thoughtful Gifting Made Easy – Perfect for Every Occasion
Whether visiting family and friends, rewarding team members, or expressing gratitude to clients, China New Year gifting has never been more expressive. JM Flower's collection includes:
- Festive Floral Gifts — Symbolic blooms like orchids and pussy willow arrangements that embody growth and good fortune.
- Premium CNY Hampers — Curated baskets filled with seasonal treats and elements that celebrate abundance and joy.
- Corporate & Personal Gift Sets — Flexible options for businesses seeking memorable client gifts or staff appreciation presents.
Each CNY gift is designed to suit diverse tastes and budgets — from compact, affordable tokens to luxurious hampers that make a statement at family gatherings, open houses, and corporate events.
Festivity and Meaning in Every Gift
Chinese New Year is more than a celebration — it's an expression of tradition, renewal, and goodwill. Thoughtfully chosen gifts are a way to share prosperity and send warm wishes for the year ahead. Hampers — especially those filled with auspicious treats and symbolic items — have become a cherished choice in Singapore's gifting culture, conveying intent and connection beyond words alone.
"We believe that every gift tells a story of care and intention. Our CNY gifts and hampers are curated to express those sentiments with beauty and quality," said a spokesperson for JM Flower.
Convenient and Reliable Delivery
With same-day delivery options available, customers can shop with ease knowing their festive gifts will arrive fresh and on time — perfect for last-minute planners and larger event orders.
Explore the full range today at https://jm.com.sg/collections/cny-gifts-hampers and make this Chinese New Year truly unforgettable with gifts that speak from the heart.
About JM Flower
JM Flower is a Singapore-based florist and gift curator specialising in elevated floral designs, seasonal gift collections, and tailored corporate gifting solutions. Known for blending traditional symbols with contemporary aesthetics, JM Flower makes meaningful gifting accessible and beautiful.
** The press release content is from PR Newswire. Bastille Post is not involved in its creation. **
Celebrate Prosperity with Exclusive Chinese New Year Gifts & Hampers from JM Flower
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REDWOOD CITY, Calif., Jan. 31, 2026 /PRNewswire/ -- Zilliz, the company behind the leading open-source vector database Milvus, today announced the open-source release of its Bilingual Semantic Highlighting Model, an industry-first AI model designed to dramatically reduce token usage and improve answer quality in production RAG-powered AI applications.
This highlighting model introduces sentence-level relevance filtering, enabling AI developers to remove low-signal context before sending prompts to large language models. This approach directly addresses rising inference costs and accuracy issues caused by oversized context windows in enterprise RAG and RAG-powered AI deployments.
"As RAG systems move into production, teams are running into very real cost and quality limits," said James Luan, VP of Engineering at Zilliz. "This model gives developers a practical way to reduce prompt size and improve answer accuracy without reworking their existing pipelines."
Key Innovations and Technical Breakthroughs
- Bilingual relevance by design: Optimized for both English and Chinese, the model addresses cross-lingual relevance challenges common in global RAG deployments. It is built on the MiniCPM-2B architecture, enabling low-latency, production-ready performance.
- Sentence-level context filtering: Rather than scoring entire document chunks, the model evaluates relevance at the sentence level and retains only content that directly supports a user query before sending it to the LLM.
- Lower token usage, higher answer quality: Zilliz reports that sentence-level filtering significantly compresses prompt size while improving downstream response quality, helping teams reduce inference costs and improve generation speed in production environments.
Availability
The Bilingual Semantic Highlighting Model is available today as an open-source release. To learn more about the training methodology and performance benchmarks, visit the Zilliz Technical Blog.
Download: : zilliz/semantic-highlight-bilingual-v1
About Zilliz
Zilliz is the company behind Milvus, the world's most widely adopted open-source vector database. Zilliz Cloud brings that performance to production with a fully managed, cloud-native platform built for scalable, low-latency vector search and hybrid retrieval. It supports billion-scale workloads with sub-10ms latency, auto-scaling, and optimized indexes for GenAI use cases like semantic search and RAG.
Zilliz is built to make AI not just possible—but practical. With a focus on performance and cost-efficiency, it helps engineering teams move from prototype to production without overprovisioning or complex infrastructure. Over 10,000 organizations worldwide rely on Zilliz to build intelligent applications at scale.
Headquartered in Redwood Shores, California, Zilliz is backed by leading investors, including Aramco's Prosperity 7 Ventures, Temasek's Pavilion Capital, Hillhouse Capital, 5Y Capital, Yunqi Partners, Trustbridge Partners, and others. Learn more at Zilliz.com.
REDWOOD CITY, Calif., Jan. 31, 2026 /PRNewswire/ -- Zilliz, the company behind the leading open-source vector database Milvus, today announced the open-source release of its Bilingual Semantic Highlighting Model, an industry-first AI model designed to dramatically reduce token usage and improve answer quality in production RAG-powered AI applications.
This highlighting model introduces sentence-level relevance filtering, enabling AI developers to remove low-signal context before sending prompts to large language models. This approach directly addresses rising inference costs and accuracy issues caused by oversized context windows in enterprise RAG and RAG-powered AI deployments.
"As RAG systems move into production, teams are running into very real cost and quality limits," said James Luan, VP of Engineering at Zilliz. "This model gives developers a practical way to reduce prompt size and improve answer accuracy without reworking their existing pipelines."
Key Innovations and Technical Breakthroughs
- Bilingual relevance by design: Optimized for both English and Chinese, the model addresses cross-lingual relevance challenges common in global RAG deployments. It is built on the MiniCPM-2B architecture, enabling low-latency, production-ready performance.
- Sentence-level context filtering: Rather than scoring entire document chunks, the model evaluates relevance at the sentence level and retains only content that directly supports a user query before sending it to the LLM.
- Lower token usage, higher answer quality: Zilliz reports that sentence-level filtering significantly compresses prompt size while improving downstream response quality, helping teams reduce inference costs and improve generation speed in production environments.
Availability
The Bilingual Semantic Highlighting Model is available today as an open-source release. To learn more about the training methodology and performance benchmarks, visit the Zilliz Technical Blog.
Download: : zilliz/semantic-highlight-bilingual-v1
About Zilliz
Zilliz is the company behind Milvus, the world's most widely adopted open-source vector database. Zilliz Cloud brings that performance to production with a fully managed, cloud-native platform built for scalable, low-latency vector search and hybrid retrieval. It supports billion-scale workloads with sub-10ms latency, auto-scaling, and optimized indexes for GenAI use cases like semantic search and RAG.
Zilliz is built to make AI not just possible—but practical. With a focus on performance and cost-efficiency, it helps engineering teams move from prototype to production without overprovisioning or complex infrastructure. Over 10,000 organizations worldwide rely on Zilliz to build intelligent applications at scale.
Headquartered in Redwood Shores, California, Zilliz is backed by leading investors, including Aramco's Prosperity 7 Ventures, Temasek's Pavilion Capital, Hillhouse Capital, 5Y Capital, Yunqi Partners, Trustbridge Partners, and others. Learn more at Zilliz.com.
** The press release content is from PR Newswire. Bastille Post is not involved in its creation. **
Zilliz Open Sources Industry-First Bilingual "Semantic Highlighting" Model to Slash RAG Token Costs and Boost Accuracy
