MAROKO133 Hot ai: Salesforce rolls out new Slackbot AI agent as it battles Microsoft and G

📌 MAROKO133 Eksklusif ai: Salesforce rolls out new Slackbot AI agent as it battles

Salesforce on Tuesday launched an entirely rebuilt version of Slackbot, the company's workplace assistant, transforming it from a simple notification tool into what executives describe as a fully powered AI agent capable of searching enterprise data, drafting documents, and taking action on behalf of employees.

The new Slackbot, now generally available to Business+ and Enterprise+ customers, is Salesforce's most aggressive move yet to position Slack at the center of the emerging "agentic AI" movement — where software agents work alongside humans to complete complex tasks. The launch comes as Salesforce attempts to convince investors that artificial intelligence will bolster its products rather than render them obsolete.

"Slackbot isn't just another copilot or AI assistant," said Parker Harris, Salesforce co-founder and Slack's chief technology officer, in an exclusive interview with Salesforce. "It's the front door to the agentic enterprise, powered by Salesforce."

From tricycle to Porsche: Salesforce rebuilt Slackbot from the ground up

Harris was blunt about what distinguishes the new Slackbot from its predecessor: "The old Slackbot was, you know, a little tricycle, and the new Slackbot is like, you know, a Porsche."

The original Slackbot, which has existed since Slack's early days, performed basic algorithmic tasks — reminding users to add colleagues to documents, suggesting channel archives, and delivering simple notifications. The new version runs on an entirely different architecture built around a large language model and sophisticated search capabilities that can access Salesforce records, Google Drive files, calendar data, and years of Slack conversations.

"It's two different things," Harris explained. "The old Slackbot was algorithmic and fairly simple. The new Slackbot is brand new — it's based around an LLM and a very robust search engine, and connections to third-party search engines, third-party enterprise data."

Salesforce chose to retain the Slackbot brand despite the fundamental technical overhaul. "People know what Slackbot is, and so we wanted to carry that forward," Harris said.

Why Anthropic's Claude powers the new Slackbot — and which AI models could come next

The new Slackbot runs on Claude, Anthropic's large language model, a choice driven partly by compliance requirements. Slack's commercial service operates under FedRAMP Moderate certification to serve U.S. federal government customers, and Harris said Anthropic was "the only provider that could give us a compliant LLM" when Slack began building the new system.

But that exclusivity won't last. "We are, this year, going to support additional providers," Harris said. "We have a great relationship with Google. Gemini is incredible — performance is great, cost is great. So we're going to use Gemini for some things." He added that OpenAI remains a possibility as well.

Harris echoed Salesforce CEO Marc Benioff's view that large language models are becoming commoditized: "You've heard Marc talk about LLMs are commodities, that they're democratized. I call them CPUs."

On the sensitive question of training data, Harris was unequivocal: Salesforce does not train any models on customer data. "Models don't have any sort of security," he explained. "If we trained it on some confidential conversation that you and I have, I don't want Carolyn to know — if I train it into the LLM, there is no way for me to say you get to see the answer, but Carolyn doesn't."

Inside Salesforce's internal experiment: 80,000 employees tested Slackbot with striking results

Salesforce has been testing the new Slackbot internally for months, rolling it out to all 80,000 employees. According to Ryan Gavin, Slack's chief marketing officer, the results have been striking: "It's the fastest adopted product in Salesforce history."

Internal data shows that two-thirds of Salesforce employees have tried the new Slackbot, with 80% of those users continuing to use it regularly. Internal satisfaction rates reached 96% — the highest for any AI feature Slack has shipped. Employees report saving between two and 20 hours per week.

The adoption happened largely organically. "I think it was about five days, and a Canvas was developed by our employees called 'The Most Stealable Slackbot Prompts,'" Gavin said. "People just started adding to it organically. I think it's up to 250-plus prompts that are in this Canvas right now."

Kate Crotty, a principal UX researcher at Salesforce, found that 73% of internal adoption was driven by social sharing rather than top-down mandates. "Everybody is there to help each other learn and communicate hacks," she said.

How Slackbot transforms scattered enterprise data into executive-ready insights

During a product demonstration, Amy Bauer, Slack's product experience designer, showed how Slackbot can synthesize information across multiple sources. In one example, she asked Slackbot to analyze customer feedback from a pilot program, upload an image of a usage dashboard, and have Slackbot correlate the qualitative and quantitative data.

"This is where Slackbot really earns its keep for me," Bauer explained. "What it's doing is not just simply reading the image — it's actually looking at the image and comparing it to the insight it just generated for me."

Slackbot can then query Salesforce to find enterprise accounts with open deals that might be good candidates for early access, creating what Bauer called "a really great justification and plan to move forward." Finally, it can synthesize all that information into a Canvas — Slack's collaborative document format — and find calendar availability among stakeholders to schedule a review meeting.

"Up until this point, we have been working in a one-to-one capacity with Slackbot," Bauer said. "But one of the benefits that I can do now is take this insight and have it generate this into a Canvas, a shared workspace where I can iterate on it, refine it with Slackbot, or share it out with my team."

Rob Seaman, Slack's chief product officer, said the Canvas creation demonstrates where the product is heading: "This is making a tool call internally to Slack Canvas to actually write, effectively, a shared document. But it signals where we're going with Slackbot — we're eventually going to be adding in additional third-party tool calls."

MrBeast's company became a Slackbot guinea pig—and employees say they're saving 90 minutes a day

Among Salesforce's pilot customers is Beast Industries, the parent company of YouTube star MrBeast. Luis Madrigal, the company's chief information officer, joined the launch announcement to describe his experience.

"As somebody who has rolled out enterprise technologies for over two decades now, this was practically one of the easiest," Madrigal …

Konten dipersingkat otomatis.

🔗 Sumber: venturebeat.com

📌 MAROKO133 Update ai: Breakthrough semiconductor manufacturing method could resha

Moving beyond the limits of conventional chip fabrication, a joint China–US research team has unveiled a semiconductor manufacturing method that could, in its words, open entirely new avenues for building high-performance light-emitting and integrated electronic devices. 

The approach is designed to overcome key weaknesses of today’s lithography-based processes, which dominate modern semiconductor production but struggle when working with fragile, next-generation materials.

In standard lithography, lasers etch circuit patterns by striking the surface vertically. However, any sideways scattering of light can lead to uncontrolled damage, a problem that becomes especially severe in soft and highly sensitive materials such as lead halide perovskites. By rethinking how structures are formed at the nanoscale, the researchers aim to enable far more precise patterning, paving the way for complex device architectures that are difficult or impossible to achieve with existing tools.

Researchers overcome machining limits in soft 2D perovskite materials

Long viewed as a breakthrough material for next-generation electronics, lead halide perovskites offer exceptional optoelectronic performance when arranged in a two-dimensional crystal lattice. Yet their soft, chemically unstable nature has made precise machining at the nanoscale extremely difficult, limiting their use in advanced semiconductor devices, the South China Morning Post writes.

An international research team spanning China and the US has reported these new findings in Nature, following a collaboration between the University of Science and Technology of China in Hefei, ShanghaiTech University, and Purdue University. The newly developed process overcomes this barrier by forming controlled lateral microstructures directly within the material.

Designed for rigid, inorganic materials, traditional semiconductor processing methods often prove too aggressive for delicate 2D perovskites. Techniques such as photolithography – which uses light to pattern surfaces – and the application of strong chemical solvents can easily damage or degrade these soft, unstable materials.

Seeking a solution that would not compromise these fragile materials, the international research team introduced a gentler fabrication approach known as self-etching. The method, which the researchers describe as transcending the limitations of traditional craftsmanship, enables precise patterning without the damage caused by conventional techniques.

Costly lithography still dominates next-generation chip manufacturing

Advanced chip manufacturing remains heavily constrained by its reliance on complex and costly equipment, especially in micro- and nano-scale fabrication. According to a Chinese expert in semiconductor device integration and design at a leading European company, the industry still depends on extreme ultraviolet (EUV) lithography systems and highly sophisticated etching tools to achieve state-of-the-art results. This deep dependence on traditional processes, the expert noted, has become a structural bottleneck as manufacturers push toward smaller, more complex device architectures.

Describing the significance of the findings, Zhang Shuchen, a materials scientist at the University of Science and Technology of China and lead author of the study, said in comments to state news agency Xinhua on January 16 that the work had created a new material platform and design pathway for high-performance luminescent and display devices.

The self-etching technique takes advantage of the internal stress that naturally builds up inside a perovskite crystal as it grows. Rather than forcing cuts from the outside, the process works from within – similar to using a hidden fault line in rock to guide precise, controlled fractures.

Using this approach, the team was able to create pixel-like units whose colour and brightness could be precisely adjusted. This led to a single crystal wafer that looks like a mosaic, made up of different perovskite regions, each with its own light-emitting behaviour. Furthermore, this level of control marks a crucial step toward smaller, more efficient optoelectronic devices, including next-generation displays and light-emitting diodes.

🔗 Sumber: interestingengineering.com