BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

​Probiotics for Augmenting Health

Background: The probiotic microorganism consists mostly of the strains of the genera Lactobacillus and Bifidobacteria. Bifidobacterial species are common members of the infant gut where they form up to 91 per cent of the total micro flora in breast-fed babies and up to 75 per cent in formula fed infants Methods: Bifidobacterial species were isolated and identified from the faeces of breast fed infants by molecular techniques. Molecular tools like 16S rDNA targeted genus and species specific mPCR primers were used for confirmation. A total of 4 isolates were identified namely B. longum (IB10 and IB12) B. breve (IB39) and B. bifidum (IB42). The identified species were screened for probiotic properties like bile tolerance, antimicrobial activity and tolerance to acidity. Ideal isolate of B. longum was incorporated in the preparation of whey based malted nutraceutical spray dried food and fed to weaned piglets. Result: B. longum (IB10) was the ideal probiotic when compared to other isolates as it had maximum antimicrobial activity and tolerance to bile and acidity. It was noted that isolate IB10 (B. longum) had an inhibitory zone ranging from 3.03 to 2.95 mm against B. cereus, S. aureus, E. coli and P. aeruginosa due to acid and antibacterial compounds. Isolate B. longum (IB10) was incorporated in the preparation of whey based malted nutraceutical spray dried food. The influence of feeding five grams of the spray dried nutraceutical malt food containing B. longum at 107cfu/g per day on animal production, gut health and gut architecture in young weaned piglets were also investigated. The probiotic regime had positive effects on the health of piglets when compared to the control group. A significant two log reduction in the coliform count was observed in the faeces of weaned piglets fed with Bifidobacterial nutraceutical powder than that of control. Thus, these probiotic bifidobacteria can be considered as safe adjuncts for preparation of dairy nutraceuticals. </jats:p

Effect of prebiotics on bifidobacterial species isolated from infant faeces

285-289The present study was conducted to evaluate the effect of prebiotics on the growth of bifidobacterial species isolated from the faeces of breast fed infants. Identification of isolates to the genus level was based on phenotypic characteristics like the unique pleomorphic morphology and carbohydrates fermentation profile. Molecular tools like species specific mPCR primers were used for confirmation. A total of 4 isolates were identified namely B. longum <i style="mso-bidi-font-style: normal">(IB10 and IB12), <i style="mso-bidi-font-style: normal">B. breve (IB39) and <i style="mso-bidi-font-style: normal">B. bifidum (IB42). Addition of 4 % WPC was used to enhance the growth of Bifidobacteria in bovine whey. Prebiotics like inulin and honey at 0.4 and 3 %, respectively were adjudged as the optimum level for exerting maximum prebiotic activity on all the four bifidobacterial isolates

Probiotic activity of Bifidobacteria from infant faeces

In the present study four isolates belonging to three bifidobacterial species with probiotic properties were isolated and identified from the faeces of breast fed infants and incorporated in the preparation of a nutraceutical whey based malt food. Identification of isolates to the genus Bifidobacteria was based on phenotypic characteristics like the unique pleomorphic morphology and carbohydrate fermentation profile. Molecular tools like 16S rRNA targeted genus and species specific mPCR were used for confirmation. The four isolates (of 3 species) identified wereB. longum(IB10 and IB12)B. breve (IB39)and B.bifidum (IB42). The nucleotide sequences of the identified species were submitted to the GenBank for acquisition of accession number. The identified species were screened for probiotic properties like bile tolerance, antimicrobial activity and tolerance to acidity. All the four isolates showed more than 80 per cent viability in the presence of 0.4, 0.8 and 1 per cent of bile salt. IsolateB.longum (IB10)showed maximum antimicrobial activity against Bacillus cereus (zi3.03 ± 0.019 mm), Staphylococcus aureus (zi3.00 ± 0.031mm), Escherichia coli(zi2.98 ± 0.043 mm) and Pseudomonas aeruginosa (zi3.03 ± 0.051 mm) in the cell free supernatant. All the four bifidobacterial isolatesshowed more than 80 per centviability atpH 3.B.longum (IB10)was a better probiotic when compared to other isolates as it had maximum antimicrobial activity and tolerance to bile and acidity.</jats:p

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License